url stringlengths 36 82 | name stringlengths 2 143 | full_name stringlengths 2 143 ⌀ | description stringlengths 0 9.95k | paper dict | introduced_year int64 1.95k 2.02k | source_url stringlengths 32 228 ⌀ | source_title stringlengths 9 170 ⌀ | code_snippet_url stringclasses 464
values | num_papers int64 0 37.4k | collections listlengths 0 6 |
|---|---|---|---|---|---|---|---|---|---|---|
https://paperswithcode.com/method/what-is-the-phone-number-for-royal-caribbean-3 | What is the phone number for Royal Caribbean group travel? @GET NOW 9am-7pm | What is the phone number for Royal Caribbean group travel? @GET NOW 9am-7pm | The phone number for Royal Caribbean group travel bookings (for 8 or more staterooms) is +1-855-732-4023 (USA) OR +44-289-708-0062 (UK). This number is available Monday-Friday from 9am-7pm and Saturday from 9am-6pm (EST).
If you would like to make a group reservation for more than 4 rooms, please call our customer s... | {
"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/faqs-usa-number-how-do-i-contact-seabourn | [[FAQS*USA*Number]] How do I contact Seabourn Cruise Line? | [[FAQS*USA*Number]] How do I contact Seabourn Cruise Line? | Costumers can speak to the Seabourn customer service team by dialing +1-855-732-4023 or +1-808-900-8011. Another number to contact international sales offices and speak to the support team is +1-855-732-4023 or +1-808-900-8011. The helpline, +1-855-732-4023 or +1-808-900-8011, is also operational for customers to get h... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/faqs-guide-24-7-how-do-i-talk-to-royal | {{FAQs=GUidE^24/7}}How do i talk to royal caribbean customer service phone number? | {{FAQs=GUidE^24/7}}How do i talk to royal caribbean customer service phone number? | General Customer Service (US & Canada): +1-855-732-4023 or +1-808-900-8011 . This number can be used for general inquiries, booking changes, and pre-cruise assistance. You can also text this number for post-cruise assistance.
Individual Reservations (US & Canada): 1-855-732-4023 or +1-808-900-8011 . Available 7 days... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/faqs-help-tm-what-number-is-800-732-4023 | [Faqs~HeLp`™]What number is 800 732 4023? | [Faqs~HeLp`™]What number is 800 732 4023? | The phone number +1-855-732-4023/ +1-855-732-4023 (USA) OR +44-289-708-0062 (UK) belongs to Royal Caribbean International’s customer service +1-855-732-4023 (USA) OR +44-289-708-0062 (UK). This toll-free number is primarily used for cruise reservations, booking inquiries, payment assistance, and general customer suppor... | {
"title": "0-1 phase transitions in sparse spiked matrix estimation",
"url": "https://paperswithcode.com/paper/0-1-phase-transitions-in-sparse-spiked-matrix"
} | 2,000 | https://arxiv.org/abs/1911.05030v1 | 0-1 phase transitions in sparse spiked matrix estimation | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/gan-hinge-loss | GAN Hinge Loss | GAN Hinge Loss | The **GAN Hinge Loss** is a hinge loss based loss function for [generative adversarial networks](https://paperswithcode.com/methods/category/generative-adversarial-networks):
$$ L\_{D} = -\mathbb{E}\_{\left(x, y\right)\sim{p}\_{data}}\left[\min\left(0, -1 + D\left(x, y\right)\right)\right] -\mathbb{E}\_{z\sim{p\_{z}... | {
"title": "Geometric GAN",
"url": "https://paperswithcode.com/paper/geometric-gan"
} | 2,000 | http://arxiv.org/abs/1705.02894v2 | Geometric GAN | https://github.com/lim0606/pytorch-geometric-gan/blob/eb84feb5cae1d6963c075aa6fb4c0c3a18eeec41/main.py#L303 | 167 | [
{
"area": "General",
"area_id": "general",
"collection": "Loss Functions"
}
] |
https://paperswithcode.com/method/can-you-transfer-a-klm-ticket-to-another | Can you transfer a KLM ticket to another person? | Can you transfer a KLM ticket to another person? | No, KLM does not allow passengers to transfer a ticket to another person +44 (20) 39000080/ 1-833-705-0001(US). Once a ticket is issued, the name on the booking cannot be changed to a different individual. KLM considers tickets non-transferable due to security and identification reasons. If you've made a spelling mista... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/oa-mix | OA-Mix | Object-Aware Mix | **OA-Mix** is a general and effective data augmentation method for single-domain generalization in object detection. It increases image diversity while preserving important semantic features with
multi-level transformations and object-aware mixing. | {
"title": "Object-Aware Domain Generalization for Object Detection",
"url": "https://paperswithcode.com/paper/object-aware-domain-generalization-for-object"
} | 2,000 | https://arxiv.org/abs/2312.12133v1 | Object-Aware Domain Generalization for Object Detection | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Image Data Augmentation"
}
] | |
https://paperswithcode.com/method/way-to-contact-silversea-cruise-refund-by | Way to Contact silversea cruise refund by phone number | Way to Contact silversea cruise refund by phone number | Based on the search results, there are a few phone numbers associated with Silversea Cruises that might be helpful when inquiring about refunds:+1-(855)-732-4023
+1-(855)-732-4023: This number is frequently mentioned in the context of cancelling a Silversea cruise and inquiring about refunds. You can call this number ... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/11-claim-ways-to-contact-expedia-customer | 11 Claim Ways to Contact Expedia Customer Service Number | 11 Claim Ways to Contact Expedia Customer Service Number | "31 Ways to Contact How can i speak to someone at Expedia Airlines- A
Step-by-Step Guide
Expedia main customer service number 1 (888) 829-0881 is 1-800-Expedia or 1 (888) 829-0881 [US-Expedia] or 1 (888) 829-0881 [UK-Expedia]
OTA (Live Person), available 24/7. This guide explains how to contact Expedia customer serv... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/way-to-talk-how-to-speak-directly-at-american | 【Way_To_TaLk】how to speak directly at American representative fast | 【Way_To_TaLk】how to speak directly at American representative fast | To speak with an American Airlines representative quickly, dial + 1-(801)-855-(5905). or + 1-(801)-855-(5905)., follow the prompts, and say "Agent" or press "0" to be connected to a representative. | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/on-social-media-support-how-do-i-talk-to-a | on social media. & Support - How do I talk to a directly At directly At American airlines representative? | on social media. & Support - How do I talk to a directly At directly At American airlines representative? | To talk to a directly At American airlines live representative in a quick time, you can initiate a request in several ways. You can call their dedicated Customer service line at “ ☎️+1-801-(855)-(5905)or +1-804-853-9001✅. (OTA) (No Wait Time),” start a chat, utilize email support, and engage on social media. | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/rmsprop | RMSProp | RMSProp | **RMSProp** is an unpublished adaptive learning rate optimizer [proposed by Geoff Hinton](http://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf). The motivation is that the magnitude of gradients can differ for different weights, and can change during learning, making it hard to choose a single global... | null | 2,013 | null | null | https://github.com/pytorch/pytorch/blob/fd8e2064e094f301d910b91a757b860aae3e3116/torch/optim/rmsprop.py#L69-L108 | 519 | [
{
"area": "General",
"area_id": "general",
"collection": "Stochastic Optimization"
}
] |
https://paperswithcode.com/method/faqs-helpline-how-do-i-call-royal-caribbean | {{FAQs_Helpline}}How do I call Royal Caribbean customer service? | {{FAQs_Helpline}}How do I call Royal Caribbean customer service? | The main customer service number for Royal Caribbean International is +1-855-732-4023 or +1-808-900-8011. If you are calling from outside the U.S. and need to contact someone on board the ship, the number is +1-855-732-4023 or +1-808-900-8011. If you are a Diamond Plus or Pinnacle Club member of the Crown & Anchor Soci... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/faq-what-is-the-cheapest-day-to-book-flights-1 | [{FAQ}]What is the cheapest day to book flights with Qatar Airways? | [{FAQ}]What is the cheapest day to book flights with Qatar Airways? | What is the cheapest day to book flights with Qatar Airways?
The cheapest days of the week to book Qatar Airways Flights are typically Tuesday, Wednesday, and Saturday +1‑833‑667‑0020 (US) or +44‑203‑970‑0065 (UK) . These are known as off-peak travel days, when demand is lower and fares are often reduced.
The che... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/faq-royal-caribbean-how-do-i-talk-to-royal | {{FAQ=Royal Caribbean@}}How do i talk to royal caribbean customer service live chat? | {{FAQ=Royal Caribbean@}}How do i talk to royal caribbean customer service live chat? | General Customer Service (US & Canada): +1-855-732-4023 or +1-808-900-8011 . This number can be used for general inquiries, booking changes, and pre-cruise assistance. You can also text this number for post-cruise assistance.
Individual Reservations (US & Canada): 1-855-732-4023 or +1-808-900-8011 . Available 7 days... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/full-guidetm-how-do-i-contact-seabourn-cruise | [Full~Guide™]How do I contact Seabourn Cruise Line? | [Full~Guide™]How do I contact Seabourn Cruise Line? | Contact your Travel Advisor or speak directly with a Seabourn representative at 855-732-4023 or +44-289-708-0062 UK. For additional ways to contact Seabourn Cruise Line, visit our Contact Us page.
Costumers can speak to the Seabourn customer service team by dialing +1-855-732-4023 and +44-289-708-0062 UK. Another nu... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/faqs-help-tm-can-i-change-my-passenger-name | [Faqs~HeLp`™]Can I change my passenger name on a Royal Caribbean cruise?? | [Faqs~HeLp`™]Can I change my passenger name on a Royal Caribbean cruise?? | Yes, you can change a passenger’s name on a Royal Caribbean cruise +1-855-732-4023 , but conditions apply. Name changes are generally allowed up to 48 hours before departure +1-855-732-4023 , though fees may apply depending on the fare type and how close it is to the sailing date. Only one name change per reservation i... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/airfare-journey-what-is-the-24-hour-rule-for | Airfare Journey"What is the 24 hour rule for Lufthansa? | Airfare Journey"What is the 24 hour rule for Lufthansa? | Travel plans can often change without warning. Using the online refund option,☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅ Lufthansa flight bookings can be cancelled and refunded online up to 24 hours before the beginning of your journey☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅. The reimbursement of the airfare is... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/what-is-the-number-for-royal-caribbean-travel | What is the number for Royal Caribbean travel agent group? | What is the number for Royal Caribbean travel agent group? | Based on the search results, here's how to contact Royal Caribbean for travel agent support:
For Travel Advisors/General Support: You can call Royal Caribbean at +1-866-562-7625 (USA) OR +44-866-562-7625 (UK). Individual Reservations booked through a Travel Agent/Agency: Call +1-866-562-7625 (USA) OR +44-866-562-762... | {
"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] | |
https://paperswithcode.com/method/local-response-normalization | Local Response Normalization | Local Response Normalization | **Local Response Normalization** is a normalization layer that implements the idea of lateral inhibition. Lateral inhibition is a concept in neurobiology that refers to the phenomenon of an excited neuron inhibiting its neighbours: this leads to a peak in the form of a local maximum, creating contrast in that area and ... | {
"title": "ImageNet Classification with Deep Convolutional Neural Networks",
"url": "https://paperswithcode.com/paper/imagenet-classification-with-deep"
} | 2,000 | http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks | ImageNet Classification with Deep Convolutional Neural Networks | https://github.com/pytorch/pytorch/blob/1c5c289b6218eb1026dcb5fd9738231401cfccea/torch/nn/modules/normalization.py#L13 | 421 | [
{
"area": "General",
"area_id": "general",
"collection": "Normalization"
}
] |
https://paperswithcode.com/method/snail | SNAIL | Simple Neural Attention Meta-Learner | The **Simple Neural Attention Meta-Learner**, or **SNAIL**, combines the benefits of temporal convolutions and attention to solve meta-learning tasks. They introduce positional dependence through temporal convolutions to make the model applicable to reinforcement tasks - where the observations, actions, and rewards are... | {
"title": "A Simple Neural Attentive Meta-Learner",
"url": "https://paperswithcode.com/paper/a-simple-neural-attentive-meta-learner"
} | 2,000 | http://arxiv.org/abs/1707.03141v3 | A Simple Neural Attentive Meta-Learner | null | 11 | [
{
"area": "Sequential",
"area_id": "sequential",
"collection": "Recurrent Neural Networks"
}
] |
https://paperswithcode.com/method/random-grayscale | Random Grayscale | Random Grayscale | **Random Grayscale** is an image data augmentation that converts an image to grayscale with probability $p$. | null | 2,000 | null | null | null | 3 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Image Data Augmentation"
}
] |
https://paperswithcode.com/method/collaborative-distillation | Collaborative Distillation | Collaborative Distillation | **Collaborative Distillation** is a new knowledge distillation method (named Collaborative Distillation) for encoder-decoder based neural style transfer to reduce the number of convolutional filters. The main idea is underpinned by a finding that the encoder-decoder pairs construct an exclusive collaborative relationsh... | {
"title": "Collaborative Distillation for Ultra-Resolution Universal Style Transfer",
"url": "https://paperswithcode.com/paper/collaborative-distillation-for-ultra"
} | 2,000 | https://arxiv.org/abs/2003.08436v2 | Collaborative Distillation for Ultra-Resolution Universal Style Transfer | null | 9 | [
{
"area": "General",
"area_id": "general",
"collection": "Knowledge Distillation"
}
] |
https://paperswithcode.com/method/21-ways-to-speak-seabourn-cruise-cancellation | 21 Ways to Speak Seabourn Cruise cancellation by Phone, Calls, Emails: A Comprehensive Guide | 21 Ways to Speak Seabourn Cruise cancellation by Phone, Calls, Emails: A Comprehensive Guide | Seabourn Cruise Cancellation Policy – Full Guide for Stress-Free Travel Changes
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/mtranse | MTransE | MTransE | {
"title": "Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment",
"url": "https://paperswithcode.com/paper/multilingual-knowledge-graph-embeddings-for"
} | 2,000 | http://arxiv.org/abs/1611.03954v3 | Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment | null | 2 | [
{
"area": "Graphs",
"area_id": "graphs",
"collection": "Graph Embeddings"
}
] | |
https://paperswithcode.com/method/james-david | James David | [@24/7-teléfono] ¿Cómo llamar a United Airlines desde Chile? | ¿Cómo llamar a United Airlines desde Chile?
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
https://paperswithcode.com/method/1-855-298-9557-what-is-the-venmo-daily-limit | +1 (855) 298-9557 What is the Venmo daily limit? | +1 (855) 298-9557 What is the Venmo daily limit? | +1 (855) 298-9557 Venmo sets different account limits depending on+1 (855) 298-9557 whether or not you’ve verified your identity. For questions about your personal limit, call +1 (855) 298-9557. Unverified users typically have a sending limit of $299.99 per week. To confirm your current cap and learn how to increase it... | {
"title": "10,000 km Straight-line Transmission using a Real-time Software-defined GPU-Based Receiver",
"url": "https://paperswithcode.com/paper/10000-km-straight-line-transmission-using-a"
} | 2,000 | https://arxiv.org/abs/2104.06311v1 | 10,000 km Straight-line Transmission using a Real-time Software-defined GPU-Based Receiver | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "6D Pose Estimation Models"
}
] |
https://paperswithcode.com/method/ncl | NCL | Neighborhood Contrastive Learning | {
"title": "Neighborhood Contrastive Learning Applied to Online Patient Monitoring",
"url": "https://paperswithcode.com/paper/neighborhood-contrastive-learning-applied-to"
} | 2,000 | https://arxiv.org/abs/2106.05142v1 | Neighborhood Contrastive Learning Applied to Online Patient Monitoring | null | 15 | [
{
"area": "General",
"area_id": "general",
"collection": "Self-Supervised Learning"
}
] | |
https://paperswithcode.com/method/72-ways-to-contact-how-do-i-change-the-name | 72 Ways to Contact How do I change the name on my Windstar reservation: A Step by Step Guide | 72 Ways to Contact How do I change the name on my Windstar reservation: A Step by Step Guide | Windstar Cruises Name Change Policy+1-855-732-4023 Guide to Passenger Name Corrections & Transfers
Planning a voyage with Windstar Cruises is an exciting experience, but if you notice a name error on your booking, contacting +1-855-732-4023 should be your first step to ensure accuracy before sailing. Windstar Cruise... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
https://paperswithcode.com/method/poto | POTO | Prediction-aware One-To-One | **Prediction-aware One-To-One**, or **POTO**, is an assignment rule for object detection which dynamically assigns the foreground samples according to the quality of classification and regression simultaneously. | {
"title": "End-to-End Object Detection with Fully Convolutional Network",
"url": "https://paperswithcode.com/paper/end-to-end-object-detection-with-fully"
} | 2,000 | https://arxiv.org/abs/2012.03544v3 | End-to-End Object Detection with Fully Convolutional Network | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Detection Assignment Rules"
}
] | |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
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} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] | |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
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} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/mixed-attention-block | Mixed Attention Block | Mixed Attention Block | **Mixed Attention Block** is an attention module used in the [ConvBERT](https://paperswithcode.com/method/convbert) architecture. It is a mixture of [self-attention](https://paperswithcode.com/method/scaled) and [span-based dynamic convolution](https://paperswithcode.com/method/span-based-dynamic-convolution) (highligh... | {
"title": "ConvBERT: Improving BERT with Span-based Dynamic Convolution",
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{
"area": "General",
"area_id": "general",
"collection": "Attention Modules"
}
] | |
https://paperswithcode.com/method/sca-cnn | SCA-CNN | Spatial and Channel-wise Attention-based Convolutional Neural Network | As CNN features are naturally spatial, channel-wise and multi-layer,
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It was designed for the task of image captioning, and uses an encoder-decoder framework where a CNN first encodes an input image into a v... | {
"title": "SCA-CNN: Spatial and Channel-wise Attention in Convolutional Networks for Image Captioning",
"url": "https://paperswithcode.com/paper/sca-cnn-spatial-and-channel-wise-attention-in"
} | 2,000 | http://arxiv.org/abs/1611.05594v2 | SCA-CNN: Spatial and Channel-wise Attention in Convolutional Networks for Image Captioning | 2 | [
{
"area": "General",
"area_id": "general",
"collection": "Attention Mechanisms"
}
] | |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
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"title": "0-1 phase transitions in sparse spiked matrix estimation",
"url": "https://paperswithcode.com/paper/0-1-phase-transitions-in-sparse-spiked-matrix"
} | 2,000 | https://arxiv.org/abs/1911.05030v1 | 0-1 phase transitions in sparse spiked matrix estimation | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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{
"area": "Reinforcement Learning",
"area_id": "reinforcement-learning",
"collection": "Off-Policy TD Control"
},
{
"area": "Reinforcement Learning",
"area_id": "reinforcement-learning",
"collection": "On-Policy TD Control"
}
] |
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"title": "0-dimensional Homology Preserving Dimensionality Reduction with TopoMap",
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} | 2,000 | https://openreview.net/forum?id=zrDNDWjOGwH | 0-dimensional Homology Preserving Dimensionality Reduction with TopoMap | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] | |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0-1 phase transitions in sparse spiked matrix estimation",
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} | 2,000 | https://arxiv.org/abs/1911.05030v1 | 0-1 phase transitions in sparse spiked matrix estimation | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Reconstruction"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 0 | [
{
"area": "General",
"area_id": "general",
"collection": "Active Learning"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks",
"url": "https://paperswithcode.com/paper/eca-net-efficient-channel-attention-for-deep"
} | 2,000 | https://arxiv.org/abs/1910.03151v4 | ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks | 5 | [
{
"area": "General",
"area_id": "general",
"collection": "Attention Mechanisms"
}
] | |
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$$
y_{tijk} = \frac{x_{tijk} - \mu_{ti}}{\sqrt{\sigma_{ti}^2 + \epsilon}},
\quad
\mu_{ti} = \frac{1}{HW}\sum_{l=1}^W \sum_{m=1}^H x_{tilm},
\quad
\sigma_{ti}^2 = \frac{1}{HW}\sum_{l=1}^W \sum_{... | {
"title": "Instance Normalization: The Missing Ingredient for Fast Stylization",
"url": "https://paperswithcode.com/paper/instance-normalization-the-missing-ingredient"
} | 2,000 | http://arxiv.org/abs/1607.08022v3 | Instance Normalization: The Missing Ingredient for Fast Stylization | https://github.com/pytorch/pytorch/blob/1c5c289b6218eb1026dcb5fd9738231401cfccea/torch/nn/modules/instancenorm.py#L141 | 572 | [
{
"area": "General",
"area_id": "general",
"collection": "Normalization"
}
] |
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{
"area": "General",
"area_id": "general",
"collection": "Regularization"
}
] | |
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"title": "Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks",
"url": "https://paperswithcode.com/paper/pade-activation-units-end-to-end-learning-of"
} | 2,000 | https://arxiv.org/abs/1907.06732v3 | Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks | null | 2 | [
{
"area": "General",
"area_id": "general",
"collection": "Adaptive Activation Functions"
},
{
"area": "General",
"area_id": "general",
"collection": "Activation Functions"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/claim-ways-to-contact-expedia-customer | Claim Ways to Contact Expedia Customer Service Number[Contact-By-USA] | Claim Ways to Contact Expedia Customer Service Number[Contact-By-USA] | "31 Ways to Contact How can i speak to someone at Expedia Airlines- A
Step-by-Step Guide
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/dolg | DOLG | Deep Orthogonal Fusion of Local and Global Features | Image Retrieval is a fundamental task of obtaining images similar to the query one from a database. A common image retrieval practice is to firstly retrieve candidate images via similarity search using global image features and then re-rank the candidates by leveraging their
local features. Previous learning-based stu... | {
"title": "DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features",
"url": "https://paperswithcode.com/paper/dolg-single-stage-image-retrieval-with-deep"
} | 2,000 | https://arxiv.org/abs/2108.02927v2 | DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Image Retrieval Models"
}
] | |
https://paperswithcode.com/method/1-855-298-9557-how-much-can-you-send-on-venmo | +1 (855) 298-9557 How much can you send on Venmo? | +1 (855) 298-9557 How much can you send on Venmo? | +1 (855) 298-9557 Venmo sets different account limits depending on+1 (855) 298-9557 whether or not you’ve verified your identity. For questions about your personal limit, call +1 (855) 298-9557. Unverified users typically have a sending limit of $299.99 per week. To confirm your current cap and learn how to increase it... | {
"title": "10,000 km Straight-line Transmission using a Real-time Software-defined GPU-Based Receiver",
"url": "https://paperswithcode.com/paper/10000-km-straight-line-transmission-using-a"
} | 2,000 | https://arxiv.org/abs/2104.06311v1 | 10,000 km Straight-line Transmission using a Real-time Software-defined GPU-Based Receiver | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Reconstruction"
}
] |
https://paperswithcode.com/method/cdil-cnn | CDIL-CNN | Circular Dilated Convolutional Neural Networks | {
"title": "Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks",
"url": "https://paperswithcode.com/paper/classification-of-long-sequential-data-using"
} | 2,000 | https://arxiv.org/abs/2201.02143v2 | Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks | null | 2 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Convolutional Neural Networks"
}
] | |
https://paperswithcode.com/method/faqs-response-how-do-i-get-a-human-at | {{faqs-response}}How do I get a human at American Airlines immediately? | {{faqs-response}}How do I get a human at American Airlines immediately? | We're dedicated to providing a positive travel experience for all customers ☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅. If you have questions or want to make special travel arrangements, you can make them online or call ☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅. For hearing or speech impaired assistance dial 711... | {
"title": "0-dimensional Homology Preserving Dimensionality Reduction with TopoMap",
"url": "https://paperswithcode.com/paper/0-dimensional-homology-preserving"
} | 2,000 | https://openreview.net/forum?id=zrDNDWjOGwH | 0-dimensional Homology Preserving Dimensionality Reduction with TopoMap | null | 0 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "6D Pose Estimation Models"
}
] |
https://paperswithcode.com/method/50-ways-to-contact-expedia-customer-service | 50 Ways to Contact Expedia Customer Service: By Phone, Email, or Online | 50 Ways to Contact Expedia Customer Service: By Phone, Email, or Online | How Do I File a Dispute with Expedia If you need to dispute a charge with Expedia, call their customer service at +1-888-829-0881 or +1-805-330-4056. For a quicker resolution, be prepared with your booking details, payment receipts, and any supporting documents when speaking with a representative.
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Reconstruction"
}
] |
https://paperswithcode.com/method/how-do-i-talk-to-royal-caribbean-customer-2 | How do I talk to Royal Caribbean customer service? FAQS-Process | How do I talk to Royal Caribbean customer service? FAQS-Process | The Royal Caribbean cancellation phone number is not provided in the search results. However, it's recommended to call their customer service line at +1-855-732-4023 or +1-808-900-8011. You can also manage your booking and potentially find cancellation information on their website.
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/mpnn | MPNN | Message Passing Neural Network | There are at least eight notable examples of models from the literature that can be described using the **Message Passing Neural Networks** (**MPNN**) framework. For simplicity we describe MPNNs which operate on undirected graphs $G$ with node features $x_{v}$ and edge features $e_{vw}$. It is trivial to extend the for... | {
"title": "Neural Message Passing for Quantum Chemistry",
"url": "https://paperswithcode.com/paper/neural-message-passing-for-quantum-chemistry"
} | 2,000 | http://arxiv.org/abs/1704.01212v2 | Neural Message Passing for Quantum Chemistry | 74 | [
{
"area": "Graphs",
"area_id": "graphs",
"collection": "Graph Models"
}
] | |
https://paperswithcode.com/method/pgnet | PGNet | Point Gathering Network | **PGNet** is a point-gathering network for reading arbitrarily-shaped text in real-time. It is a single-shot text spotter, where the pixel-level character classification map is learned with proposed PG-CTC loss avoiding the usage of character-level annotations. With a PG-CTC decoder, we gather high-level character clas... | {
"title": "PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network",
"url": "https://paperswithcode.com/paper/pgnet-real-time-arbitrarily-shaped-text"
} | 2,000 | https://arxiv.org/abs/2104.05458v1 | PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network | null | 2 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Scene Text Models"
}
] |
https://paperswithcode.com/method/augmix | AugMix | AugMix | AugMix mixes augmented images through linear interpolations. Consequently it is like [Mixup](https://paperswithcode.com/method/mixup) but instead mixes augmented versions of the same image. | {
"title": "AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty",
"url": "https://paperswithcode.com/paper/augmix-a-simple-data-processing-method-to"
} | 2,000 | https://arxiv.org/abs/1912.02781v2 | AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty | https://github.com/google-research/augmix/blob/7c84885fe064435b4b7a8b596b937f0a879e458c/augment_and_mix.py#L40 | 20 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Image Data Augmentation"
}
] |
https://paperswithcode.com/method/log-decay | Log Decay | Cyclical Log Annealing as a Learning Rate Scheduler | Cyclical log annealing make harsh restarts by creating learning rate spikes to escape a local minimum on weight bias fields while retaining the capability to hang onto a low learning rate unlike cosine annealing, which opens up a discussion of if more greedy stochastic optimization schemes could be viable without as hi... | null | 2,000 | null | null | 0 | [
{
"area": "General",
"area_id": "general",
"collection": "Learning Rate Schedules"
}
] | |
https://paperswithcode.com/method/iicnet | IICNet | IICNet | **Invertible Image Conversion Net**, or **IICNet**, is a generic framework for reversible image conversion tasks. Unlike previous encoder-decoder based methods, IICNet maintains a highly invertible structure based on invertible neural networks (INNs) to better preserve the information during conversion. It uses a relat... | {
"title": "IICNet: A Generic Framework for Reversible Image Conversion",
"url": "https://paperswithcode.com/paper/iicnet-a-generic-framework-for-reversible"
} | 2,000 | https://arxiv.org/abs/2109.04242v1 | IICNet: A Generic Framework for Reversible Image Conversion | null | 2 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Reversible Image Conversion Models"
},
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Image Models"
}
] |
https://paperswithcode.com/method/hotline-service-how-to-book-international | [Hotline~service] How to book international flight with British Airlines? | [Hotline~service] How to book international flight with British Airlines? | ☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅ is the direct line you should dial when booking any international flight with British Airlines for accurate service and hassle-free reservations. Using ☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅ ensures that you speak directly with British Airlines specialists who unders... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/scatter-connection | Scatter Connection | Scatter Connection | A **Scatter Connection** is a type of connection that allows a vector to be "scattered" onto a layer representing a map, so that a vector at a specific location corresponds to objects of interest at that location (e.g. units in Starcraft II). This allows for the integration of spatial and non-spatial features. | null | 2,000 | null | null | null | 10 | [
{
"area": "General",
"area_id": "general",
"collection": "Miscellaneous Components"
}
] |
https://paperswithcode.com/method/senet | SENet | SENet | A **SENet** is a convolutional neural network architecture that employs squeeze-and-excitation blocks to enable the network to perform dynamic channel-wise feature recalibration. | {
"title": "Squeeze-and-Excitation Networks",
"url": "https://paperswithcode.com/paper/squeeze-and-excitation-networks"
} | 2,000 | https://arxiv.org/abs/1709.01507v4 | Squeeze-and-Excitation Networks | https://github.com/osmr/imgclsmob/blob/68335927ba27f2356093b985bada0bc3989836b1/pytorch/pytorchcv/models/senet.py#L167 | 47 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Convolutional Neural Networks"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/what-is-the-phone-number-for-royal-caribbean-8 | What is the phone number for Royal Caribbean cancel? FAQS-Recommended | What is the phone number for Royal Caribbean cancel? FAQS-Recommended | The Royal Caribbean cancellation phone number is not provided in the search results. However, it's recommended to call their customer service line at +1-855-732-4023 or +1-808-900-8011. You can also manage your booking and potentially find cancellation information on their website.
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/contacto-en-vivo-como-puedo-hablar-con-una | {Contacto en vivo}¿Cómo puedo hablar con una persona de United? | {Contacto en vivo}¿Cómo puedo hablar con una persona de United? | Para hablar con una persona de United Airlines, puedes llamar al número de teléfono de atención al cliente de United. Para México, puedes marcar el +1-808-470-7107. También puedes contactarlos a través de su sitio web o app. | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
https://paperswithcode.com/method/connect-now-how-to-get-through-to-american-1 | CONNECT~NOW~How to get through to American Airlines fast? | CONNECT~NOW~How to get through to American Airlines fast? | To reach American Airlines customer service quickly,☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅ try calling during off-peak hours,☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅ using the callback option,☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅ or utilizing the live chat feature on their website or app. Also,☎️+1-... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/ultimate-solution-how-do-i-cancel-a-cruise | [[Ultimate!!Solution]]How do I cancel a cruise without penalty? | [[Ultimate!!Solution]]How do I cancel a cruise without penalty? | To cancel a cruise without penalty, the key is to understand and utilize the cruise line's cancellation policy and potentially consider travel insurance.+1-(855)-732-4023 Generally, you can cancel without penalty if you do so within a risk-free cancellation window (often 24-48 hours after booking)+1-(855)-732-4023 or i... | {
"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
https://paperswithcode.com/method/lda2vec | lda2vec | lda2vec | **lda2vec** builds representations over both words and documents by mixing word2vec’s skipgram architecture with Dirichlet-optimized sparse topic mixtures.
The Skipgram Negative-Sampling (SGNS) objective of word2vec is modified to utilize document-wide feature vectors while simultaneously learning continuous docume... | {
"title": "Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vec",
"url": "https://paperswithcode.com/paper/mixing-dirichlet-topic-models-and-word"
} | 2,000 | http://arxiv.org/abs/1605.02019v1 | Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vec | null | 1 | [
{
"area": "Natural Language Processing",
"area_id": "natural-language-processing",
"collection": "Topic Embeddings"
},
{
"area": "Natural Language Processing",
"area_id": "natural-language-processing",
"collection": "Document Embeddings"
},
{
"area": "Natural Language Processing"... |
https://paperswithcode.com/method/mincutpool | MinCutPool | MinCut Pooling | MinCutPool is a trainable pooling operator for graphs that learns to map nodes into clusters.
The method is trained to approximate the minimum K-cut of the graph to ensure that the clusters are balanced, while also jointly optimizing the objective of the task at hand. | {
"title": "Spectral Clustering with Graph Neural Networks for Graph Pooling",
"url": "https://paperswithcode.com/paper/mincut-pooling-in-graph-neural-networks"
} | 2,000 | https://arxiv.org/abs/1907.00481v6 | Spectral Clustering with Graph Neural Networks for Graph Pooling | 2 | [
{
"area": "Graphs",
"area_id": "graphs",
"collection": "Graph Models"
}
] | |
https://paperswithcode.com/method/faqs-guide-how-does-royal-caribbean-cancel | [FAQS=GUide]How does Royal Caribbean cancel for any reason work? | [FAQS=GUide]How does Royal Caribbean cancel for any reason work? | The phone number to contact Royal Caribbean customer service for cruise cancellations is 1-855-732-4023 or 1-808-900-8011. Pre-Cruise Planning Assistance: 1-855-732-4023 or 1-808-900-8011 Consumer Outreach Team: 1-855-732-4023 or 1-808-900-8011 (for booking changes, if booked directly) It's always recommended to consul... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/mfr | MFR | Meta Face Recognition | **Meta Face Recognition** (MFR) is a meta-learning face recognition method. MFR synthesizes the source/target domain shift with a meta-optimization objective, which requires the model to learn effective representations not only on synthesized source domains but also on synthesized target domains. Specifically, domain-s... | {
"title": "Learning Meta Face Recognition in Unseen Domains",
"url": "https://paperswithcode.com/paper/learning-meta-face-recognition-in-unseen"
} | 2,000 | https://arxiv.org/abs/2003.07733v2 | Learning Meta Face Recognition in Unseen Domains | null | 19 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Face Recognition Models"
}
] |
https://paperswithcode.com/method/dense-contrastive-learning | Dense Contrastive Learning | Dense Contrastive Learning | **Dense Contrastive Learning** is a self-supervised learning method for dense prediction tasks. It implements self-supervised learning by optimizing a pairwise contrastive (dis)similarity loss at the pixel level between two views of input images. Contrasting with regular contrastive loss, the contrastive loss is comput... | {
"title": "Dense Contrastive Learning for Self-Supervised Visual Pre-Training",
"url": "https://paperswithcode.com/paper/dense-contrastive-learning-for-self"
} | 2,000 | https://arxiv.org/abs/2011.09157v2 | Dense Contrastive Learning for Self-Supervised Visual Pre-Training | null | 9 | [
{
"area": "General",
"area_id": "general",
"collection": "Self-Supervised Learning"
}
] |
https://paperswithcode.com/method/1-855-298-9557-what-is-the-venmo-debit-card | +1 (855) 298-9557 What is the Venmo debit card limit? | +1 (855) 298-9557 What is the Venmo debit card limit? | +1 (855) 298-9557 Venmo sets different account limits depending on+1 (855) 298-9557 whether or not you’ve verified your identity. For questions about your personal limit, call +1 (855) 298-9557. Unverified users typically have a sending limit of $299.99 per week. To confirm your current cap and learn how to increase it... | {
"title": "10,000 km Straight-line Transmission using a Real-time Software-defined GPU-Based Receiver",
"url": "https://paperswithcode.com/paper/10000-km-straight-line-transmission-using-a"
} | 2,000 | https://arxiv.org/abs/2104.06311v1 | 10,000 km Straight-line Transmission using a Real-time Software-defined GPU-Based Receiver | null | 1 | [
{
"area": "Reinforcement Learning",
"area_id": "reinforcement-learning",
"collection": "Actor-Critic Algorithms"
}
] |
https://paperswithcode.com/method/74-ways-to-connect-can-i-change-the-name-of-a | 74 Ways to Connect Can I change the name of a passenger on a Viking cruise: A Step by Step Guide | 74 Ways to Connect Can I change the name of a passenger on a Viking cruise: A Step by Step Guide | Viking Cruises Name Change Policy+1-855-732-4023 Guide to Passenger Name Corrections & Transfers
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/faqs-guideline-how-do-i-get-a-refund-from | [Faqs`Guideline]How do I get a refund from Disney Cruise? | [Faqs`Guideline]How do I get a refund from Disney Cruise? | To request a refund from Disney Cruise Line, you'll generally need to contact them directly by phone or email. +1-855-732-4023 If Disney cancels or delays your cruise significantly,1-808-900-8011 you can email Caserequest@disneycruise.com for assistance with refunds or cruise credits. You can also call +1-855-732-4023 ... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
https://paperswithcode.com/method/inception-module | Inception Module | Inception Module | An **Inception Module** is an image model block that aims to approximate an optimal local sparse structure in a CNN. Put simply, it allows for us to use multiple types of filter size, instead of being restricted to a single filter size, in a single image block, which we then concatenate and pass onto the next layer. | {
"title": "Going Deeper with Convolutions",
"url": "https://paperswithcode.com/paper/going-deeper-with-convolutions"
} | 2,000 | http://arxiv.org/abs/1409.4842v1 | Going Deeper with Convolutions | https://github.com/hskang9/Googlenet/blob/654d126b6a2cd3ac944cf5613419deb73da5311e/keras/googlenet.py#L39 | 206 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Image Model Blocks"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
"area": "General",
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}
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
"area": "General",
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{
"area": "General",
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{
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
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{
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | 2 | [
{
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{
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{
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{
"area": "General",
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"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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