paper_url stringlengths 36 81 | paper_title stringlengths 1 242 ⌀ | paper_arxiv_id stringlengths 9 16 ⌀ | paper_url_abs stringlengths 18 314 | paper_url_pdf stringlengths 21 935 ⌀ | repo_url stringlengths 26 200 | is_official bool 2
classes | mentioned_in_paper bool 2
classes | mentioned_in_github bool 2
classes | framework stringclasses 9
values |
|---|---|---|---|---|---|---|---|---|---|
https://paperswithcode.com/paper/robotic-pick-and-place-of-novel-objects-in | Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching | 1710.01330 | https://arxiv.org/abs/1710.01330v5 | https://arxiv.org/pdf/1710.01330v5.pdf | https://github.com/andyzeng/arc-robot-vision | true | false | true | torch |
https://paperswithcode.com/paper/bert-pre-training-of-deep-bidirectional | BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding | 1810.04805 | https://arxiv.org/abs/1810.04805v2 | https://arxiv.org/pdf/1810.04805v2.pdf | https://github.com/MLH-Fellowship/Social-BERTerfly | false | false | true | tf |
https://paperswithcode.com/paper/automatic-differentiation-of-sylvester | Automatic differentiation of Sylvester, Lyapunov, and algebraic Riccati equations | 2011.11430 | https://arxiv.org/abs/2011.11430v2 | https://arxiv.org/pdf/2011.11430v2.pdf | https://github.com/tachukao/autodiff-inverse-lqr | true | true | true | none |
https://paperswithcode.com/paper/sensing-ambiguity-in-henry-james-the-turn-of | Sensing Ambiguity in Henry James' "The Turn of the Screw" | 2011.10832 | https://arxiv.org/abs/2011.10832v1 | https://arxiv.org/pdf/2011.10832v1.pdf | https://github.com/vicmak/TurnOfTheScrew | true | true | false | none |
https://paperswithcode.com/paper/two-stage-generative-adversarial-networks-for | Two-stage generative adversarial networks for document image binarization with color noise and background removal | 2010.10103 | https://arxiv.org/abs/2010.10103v3 | https://arxiv.org/pdf/2010.10103v3.pdf | https://github.com/opensuh/DocumentBinarization | true | true | true | pytorch |
https://paperswithcode.com/paper/supervised-edge-attention-network-for | Supervised Edge Attention Network for Accurate Image Instance Segmentation | null | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5884_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123720613.pdf | https://github.com/IPIU-detection/SEANet | true | false | false | pytorch |
https://paperswithcode.com/paper/teacher-student-consistency-for-multi-source | Teacher-Student Consistency For Multi-Source Domain Adaptation | 2010.10054 | https://arxiv.org/abs/2010.10054v1 | https://arxiv.org/pdf/2010.10054v1.pdf | https://github.com/amosy3/MUST | true | true | false | pytorch |
https://paperswithcode.com/paper/mesh-denoising-with-facet-graph-convolutions | Mesh Denoising with Facet Graph Convolutions | null | https://github.com/Elensil/Facet_Graph_Convolution#abstract | https://hal.inria.fr/hal-03066322 | https://github.com/Elensil/Facet_Graph_Convolution | false | false | false | tf |
https://paperswithcode.com/paper/counterfactual-multi-agent-policy-gradients | Counterfactual Multi-Agent Policy Gradients | 1705.08926 | https://arxiv.org/abs/1705.08926v3 | https://arxiv.org/pdf/1705.08926v3.pdf | https://github.com/opendilab/DI-engine/blob/main/ding/policy/coma.py | false | false | false | pytorch |
https://paperswithcode.com/paper/confnet2seq-full-length-answer-generation | ConfNet2Seq: Full Length Answer Generation from Spoken Questions | 2006.05163 | https://arxiv.org/abs/2006.05163v2 | https://arxiv.org/pdf/2006.05163v2.pdf | https://github.com/kolk/ConfnetPointerGenBaseline | true | true | true | pytorch |
https://paperswithcode.com/paper/mmdetection-open-mmlab-detection-toolbox-and | MMDetection: Open MMLab Detection Toolbox and Benchmark | 1906.07155 | https://arxiv.org/abs/1906.07155v1 | https://arxiv.org/pdf/1906.07155v1.pdf | https://github.com/IPIU-detection/SEANet | false | false | true | pytorch |
https://paperswithcode.com/paper/joint-multi-leaf-segmentation-alignment-and | Joint Multi-Leaf Segmentation, Alignment and Tracking from Fluorescence Plant Videos | 1505.00353 | http://arxiv.org/abs/1505.00353v2 | http://arxiv.org/pdf/1505.00353v2.pdf | https://github.com/xiyinmsu/PlantVision | true | false | false | none |
https://paperswithcode.com/paper/meta-reinforcement-learning-by-tracking-task | Meta-Reinforcement Learning by Tracking Task Non-stationarity | 2105.08834 | https://arxiv.org/abs/2105.08834v1 | https://arxiv.org/pdf/2105.08834v1.pdf | https://github.com/riccardopoiani/trio-non-stationary-meta-rl | true | true | false | pytorch |
https://paperswithcode.com/paper/rotate-to-attend-convolutional-triplet | Rotate to Attend: Convolutional Triplet Attention Module | 2010.03045 | https://arxiv.org/abs/2010.03045v2 | https://arxiv.org/pdf/2010.03045v2.pdf | https://github.com/LandskapeAI/triplet-attention | true | true | true | pytorch |
https://paperswithcode.com/paper/efficient-sampling-policy-for-selecting-a | Efficient Sampling Policy for Selecting a Good Enough Subset | 2111.14534 | https://arxiv.org/abs/2111.14534v1 | https://arxiv.org/pdf/2111.14534v1.pdf | https://github.com/gongbozhang-pku/Good-Enough-Selection | true | false | false | none |
https://paperswithcode.com/paper/autofocus-layer-for-semantic-segmentation | Autofocus Layer for Semantic Segmentation | 1805.08403 | http://arxiv.org/abs/1805.08403v3 | http://arxiv.org/pdf/1805.08403v3.pdf | https://github.com/luvgold/auotofoucus3D-Brats | false | false | true | tf |
https://paperswithcode.com/paper/bengali-abstractive-news-summarization-bans-a | Bengali Abstractive News Summarization(BANS): A Neural Attention Approach | 2012.01747 | https://arxiv.org/abs/2012.01747v1 | https://arxiv.org/pdf/2012.01747v1.pdf | https://github.com/Prithwiraj12/Bengali-Deep-News-Summarization | true | true | false | tf |
https://paperswithcode.com/paper/transferable-visual-words-exploiting-the | Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning | 2102.10680 | https://arxiv.org/abs/2102.10680v1 | https://arxiv.org/pdf/2102.10680v1.pdf | https://github.com/JLiangLab/TransVW | true | true | true | pytorch |
https://paperswithcode.com/paper/locally-checkable-problems-in-rooted-trees | Locally Checkable Problems in Rooted Trees | 2102.09277 | https://arxiv.org/abs/2102.09277v5 | https://arxiv.org/pdf/2102.09277v5.pdf | https://github.com/jendas1/rooted-tree-classifier | true | true | false | none |
https://paperswithcode.com/paper/sprint-ultrafast-protein-protein-interaction | SPRINT: Ultrafast protein-protein interaction prediction of the entire human interactome | 1705.06848 | http://arxiv.org/abs/1705.06848v1 | http://arxiv.org/pdf/1705.06848v1.pdf | https://github.com/lucian-ilie/SPRINT | true | true | false | none |
https://paperswithcode.com/paper/profiler-a-fast-and-versatile-new-program-for | $Profiler$ - A Fast and Versatile New Program for Decomposing Galaxy Light Profiles | 1607.08620 | http://arxiv.org/abs/1607.08620v1 | http://arxiv.org/pdf/1607.08620v1.pdf | https://github.com/BogdanCiambur/PROFILER | true | true | false | none |
https://paperswithcode.com/paper/cell-veto-monte-carlo-algorithm-for-long | Cell-veto Monte Carlo algorithm for long-range systems | 1606.06780 | http://arxiv.org/abs/1606.06780v2 | http://arxiv.org/pdf/1606.06780v2.pdf | https://github.com/Cell-veto/postlhc | true | true | false | none |
https://paperswithcode.com/paper/an-accelerometer-based-calculator-for | An Accelerometer Based Calculator for Visually Impaired People Using Mobile Devices | 1604.07660 | http://arxiv.org/abs/1604.07660v1 | http://arxiv.org/pdf/1604.07660v1.pdf | https://github.com/ereneld/accelerometerbasedcalculatorios | true | true | false | none |
https://paperswithcode.com/paper/identification-of-port-hamiltonian-systems | Identification of Port-Hamiltonian Systems from Frequency Response Data | 1911.00080 | https://arxiv.org/abs/1911.00080v1 | https://arxiv.org/pdf/1911.00080v1.pdf | https://github.com/mpimd-csc/Identify_PortHamiltonian_Realization | false | false | true | none |
https://paperswithcode.com/paper/using-gaia-dr2-to-constrain-local-dark-matter | Using Gaia DR2 to Constrain Local Dark Matter Density and Thin Dark Disk | 1808.05603 | https://arxiv.org/abs/1808.05603v2 | https://arxiv.org/pdf/1808.05603v2.pdf | https://github.com/bbsonjohn/darkdisk | false | false | true | none |
https://paperswithcode.com/paper/githru-visual-analytics-for-understanding | Githru: Visual Analytics for Understanding Software Development History Through Git Metadata Analysis | 2009.03115 | https://arxiv.org/abs/2009.03115v2 | https://arxiv.org/pdf/2009.03115v2.pdf | https://github.com/githru/githru | true | true | true | none |
https://paperswithcode.com/paper/a-gaia-dr2-view-of-the-open-cluster | A Gaia DR2 view of the Open Cluster population in the Milky Way | 1805.08726 | https://arxiv.org/abs/1805.08726v2 | https://arxiv.org/pdf/1805.08726v2.pdf | https://github.com/ignotur/Random-forest-open-cluster | false | false | true | none |
https://paperswithcode.com/paper/on-hypothesis-testing-trials-factor | On hypothesis testing, trials factor, hypertests and the BumpHunter | 1101.0390 | https://arxiv.org/abs/1101.0390v2 | https://arxiv.org/pdf/1101.0390v2.pdf | https://github.com/lovaslin/pyBumpHunter | false | false | true | none |
https://paperswithcode.com/paper/client-based-control-channel-analysis-for | Client-Based Control Channel Analysis for Connectivity Estimation in LTE Networks | 1701.03304 | https://arxiv.org/abs/1701.03304v1 | https://arxiv.org/pdf/1701.03304v1.pdf | https://github.com/falkenber9/falcon | false | false | true | none |
https://paperswithcode.com/paper/discover-your-competition-in-lte-client-based | Discover Your Competition in LTE: Client-Based Passive Data Rate Prediction by Machine Learning | 1711.06820 | https://arxiv.org/abs/1711.06820v2 | https://arxiv.org/pdf/1711.06820v2.pdf | https://github.com/falkenber9/falcon | false | false | true | none |
https://paperswithcode.com/paper/problem-agnostic-speech-embeddings-for-multi | Problem-Agnostic Speech Embeddings for Multi-Speaker Text-to-Speech with SampleRNN | 1906.00733 | https://arxiv.org/abs/1906.00733v3 | https://arxiv.org/pdf/1906.00733v3.pdf | https://github.com/santi-pdp/pase | false | false | true | pytorch |
https://paperswithcode.com/paper/mugnet-multi-resolution-graph-neural-network | MuGNet: Multi-Resolution Graph Neural Network for Large-Scale Pointcloud Segmentation | null | https://arxiv.org/abs/2009.08924?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%253A+arxiv%252FQSXk+%2528ExcitingAds%2521+cs+updates+on+arXiv.org%2529 | https://arxiv.org/abs/2009.08924?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%253A+arxiv%252FQSXk+%2528ExcitingAds%2521+cs+updates+on+arXiv.org%2529 | https://github.com/liuyuex97/MuGNet | true | false | false | pytorch |
https://paperswithcode.com/paper/implementing-perceptron-models-with-qubits | Implementing perceptron models with qubits | 1905.06728 | https://arxiv.org/abs/1905.06728v2 | https://arxiv.org/pdf/1905.06728v2.pdf | https://github.com/therooler/pennylane-qllh | false | false | true | tf |
https://paperswithcode.com/paper/faster-family-wise-error-control-for | Faster Family-wise Error Control for Neuroimaging with a Parametric Bootstrap | 1708.05037 | http://arxiv.org/abs/1708.05037v2 | http://arxiv.org/pdf/1708.05037v2.pdf | https://bitbucket.org/simonvandekar/param-boot | true | true | false | none |
https://paperswithcode.com/paper/decentralized-baseband-processing-for-massive | Decentralized Baseband Processing for Massive MU-MIMO Systems | 1702.04458 | http://arxiv.org/abs/1702.04458v2 | http://arxiv.org/pdf/1702.04458v2.pdf | https://github.com/VIP-Group/DBP | true | true | false | none |
https://paperswithcode.com/paper/aerial-imagery-pixel-level-segmentation | Aerial Imagery Pixel-level Segmentation | 2012.02024 | https://arxiv.org/abs/2012.02024v1 | https://arxiv.org/pdf/2012.02024v1.pdf | https://github.com/mrheffels/aerial-imagery-segmentation | true | true | false | tf |
https://paperswithcode.com/paper/on-the-adoption-usage-and-evolution-of-kotlin | On the adoption, usage and evolution of Kotlin Features on Android development | 1907.09003 | http://arxiv.org/abs/1907.09003v3 | http://arxiv.org/pdf/1907.09003v3.pdf | https://github.com/UPHF/kotlin_features | true | true | false | none |
https://paperswithcode.com/paper/deep-learning-to-generate-in-silico-chemical | Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples | 1905.08411 | http://arxiv.org/abs/1905.08411v1 | http://arxiv.org/pdf/1905.08411v1.pdf | https://github.com/pnnl/darkchem | true | true | false | tf |
https://paperswithcode.com/paper/rowhammer-and-beyond | RowHammer and Beyond | 1903.11056 | http://arxiv.org/abs/1903.11056v1 | http://arxiv.org/pdf/1903.11056v1.pdf | https://github.com/google/rowhammer-test | true | true | false | none |
https://paperswithcode.com/paper/radynversion-learning-to-invert-a-solar-flare | RADYNVERSION: Learning to Invert a Solar Flare Atmosphere with Invertible Neural Networks | 1901.08626 | http://arxiv.org/abs/1901.08626v2 | http://arxiv.org/pdf/1901.08626v2.pdf | https://github.com/Goobley/Radynversion | true | true | false | pytorch |
https://paperswithcode.com/paper/arja-automated-repair-of-java-programs-via | ARJA: Automated Repair of Java Programs via Multi-Objective Genetic Programming | 1712.07804 | http://arxiv.org/abs/1712.07804v1 | http://arxiv.org/pdf/1712.07804v1.pdf | https://github.com/yyxhdy/SeededBugs | true | true | false | none |
https://paperswithcode.com/paper/kern | KERN | 1710.09145 | http://arxiv.org/abs/1710.09145v1 | http://arxiv.org/pdf/1710.09145v1.pdf | https://github.com/ska-sa/meqtrees-cattery | true | true | false | none |
https://paperswithcode.com/paper/re-run-repeat-reproduce-reuse-replicate | Re-run, Repeat, Reproduce, Reuse, Replicate: Transforming Code into Scientific Contributions | 1708.08205 | https://arxiv.org/abs/1708.08205v2 | https://arxiv.org/pdf/1708.08205v2.pdf | https://github.com/benureau/r5 | true | true | false | none |
https://paperswithcode.com/paper/multiscale-information-decomposition-exact | Multiscale Information Decomposition: Exact Computation for Multivariate Gaussian Processes | 1706.07136 | http://arxiv.org/abs/1706.07136v2 | http://arxiv.org/pdf/1706.07136v2.pdf | https://github.com/danielemarinazzo/multiscale_PID | true | true | false | none |
https://paperswithcode.com/paper/compressing-recurrent-neural-networks-with | Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition | 1811.07503 | http://arxiv.org/abs/1811.07503v1 | http://arxiv.org/pdf/1811.07503v1.pdf | https://github.com/tnbar/tednet | true | false | false | pytorch |
https://paperswithcode.com/paper/bayesian-adaptive-n-of-1-trials-for | Bayesian adaptive N-of-1 trials for estimating population and individual treatment effects | 1911.00878 | http://arxiv.org/abs/1911.00878v3 | http://arxiv.org/pdf/1911.00878v3.pdf | https://github.com/SenarathneSGJ/Adaptive_N-of-1_trials_design | true | true | false | none |
https://paperswithcode.com/paper/interactive-discovery-system-for-direct | Interactive Discovery System for Direct Democracy | 1807.04448 | http://arxiv.org/abs/1807.04448v1 | http://arxiv.org/pdf/1807.04448v1.pdf | https://github.com/elaragon/decide-topics | true | true | true | none |
https://paperswithcode.com/paper/encryptgan-image-steganography-with-domain | EncryptGAN: Image Steganography with Domain Transform | 1905.11582 | http://arxiv.org/abs/1905.11582v2 | http://arxiv.org/pdf/1905.11582v2.pdf | https://github.com/zhengziqiang/EncryptGAN | true | true | true | tf |
https://paperswithcode.com/paper/deep-active-inference | Deep Active Inference | 1709.02341 | http://arxiv.org/abs/1709.02341v5 | http://arxiv.org/pdf/1709.02341v5.pdf | https://github.com/kaiu85/deepAI_paper | true | true | true | none |
https://paperswithcode.com/paper/setiburst-a-robotic-commensal-realtime-multi | SETIBURST: A Robotic, Commensal, Realtime Multi-Science Backend for the Arecibo Telescope | 1701.04538 | http://arxiv.org/abs/1701.04538v1 | http://arxiv.org/pdf/1701.04538v1.pdf | https://github.com/griffinfoster/alfaburst-survey | false | false | true | none |
https://paperswithcode.com/paper/an-adaptive-partition-of-unity-method-for | An adaptive partition of unity method for multivariate Chebyshev polynomial approximations | 1805.00423 | http://arxiv.org/abs/1805.00423v3 | http://arxiv.org/pdf/1805.00423v3.pdf | https://github.com/kevinwaiton/PUchebfun | true | true | true | none |
https://paperswithcode.com/paper/hazelnut-a-bidirectionally-typed-structure | Hazelnut: A Bidirectionally Typed Structure Editor Calculus | 1607.04180 | https://arxiv.org/abs/1607.04180v5 | https://arxiv.org/pdf/1607.04180v5.pdf | https://github.com/hazelgrove/hazelnut-dynamics-agda | false | false | true | none |
https://paperswithcode.com/paper/live-functional-programming-with-typed-holes | Live Functional Programming with Typed Holes | 1805.00155 | http://arxiv.org/abs/1805.00155v4 | http://arxiv.org/pdf/1805.00155v4.pdf | https://github.com/hazelgrove/hazelnut-dynamics-agda | true | true | true | none |
https://paperswithcode.com/paper/on-location-relevance-and-diversity-in-human | On Location Relevance and Diversity in Human Mobility Data | 2010.10198 | http://arxiv.org/abs/2010.10198v1 | http://arxiv.org/pdf/2010.10198v1.pdf | https://github.com/SeqScan/SeqScan-D | true | true | false | none |
https://paperswithcode.com/paper/automatic-analysis-and-influence-of | Automatic Analysis and Influence of Hierarchical Structure on Melody, Rhythm and Harmony in Popular Music | 2010.07518 | http://arxiv.org/abs/2010.07518v1 | http://arxiv.org/pdf/2010.07518v1.pdf | https://github.com/Dsqvival/hierarchical-structure-analysis | true | true | false | none |
https://paperswithcode.com/paper/centering-noisy-images-with-application-to | Centering noisy images with application to cryo-EM | 2009.04810 | http://arxiv.org/abs/2009.04810v1 | http://arxiv.org/pdf/2009.04810v1.pdf | https://github.com/nirsharon/RACER | true | true | false | none |
https://paperswithcode.com/paper/model-selection-for-estimation-of-causal | Model selection for estimation of causal parameters | 2008.12892 | https://arxiv.org/abs/2008.12892v2 | https://arxiv.org/pdf/2008.12892v2.pdf | https://github.com/rothenhaeusler/tms | true | true | false | none |
https://paperswithcode.com/paper/macsen-a-voice-assistant-for-speakers-of-a | Macsen: A Voice Assistant for Speakers of a Lesser Resourced Language | null | https://aclanthology.org/2020.sltu-1.27 | https://aclanthology.org/2020.sltu-1.27.pdf | https://github.com/techiaith/macsen-sgwrsfot | true | false | false | none |
https://paperswithcode.com/paper/fault-slip-in-hydraulic-stimulation-of | Fault slip in hydraulic stimulation of geothermal reservoirs: governing mechanisms and process-structure interaction | 2008.11190 | https://arxiv.org/abs/2008.11190v2 | https://arxiv.org/pdf/2008.11190v2.pdf | https://github.com/IvarStefansson/Fault-Slip-in-Hydraulic-Stimulation-of-Geothermal-Reservoirs | true | true | false | none |
https://paperswithcode.com/paper/a-group-theoretic-perspective-on | A group theoretic perspective on entanglements of division fields | 2008.09886 | https://arxiv.org/abs/2008.09886v3 | https://arxiv.org/pdf/2008.09886v3.pdf | https://github.com/jmorrow4692/Entanglements | true | true | false | none |
https://paperswithcode.com/paper/on-bayesian-inference-for-the-extended | On Bayesian inference for the Extended Plackett-Luce model | 2002.05953 | http://arxiv.org/abs/2002.05953v1 | http://arxiv.org/pdf/2002.05953v1.pdf | https://github.com/srjresearch/ExtendedPL | true | true | false | none |
https://paperswithcode.com/paper/boundary-solution-based-on-rescaling-method | Boundary solution based on rescaling method: recoup the first and second-order statistics of neuron network dynamics | 2002.02381 | http://arxiv.org/abs/2002.02381v1 | http://arxiv.org/pdf/2002.02381v1.pdf | https://github.com/ceciliaromaro/recoup-the-first-and-second-order-statistics-of-neuron-network-dynamics | true | true | false | none |
https://paperswithcode.com/paper/cold-start-aware-user-and-product-attention | Cold-Start Aware User and Product Attention for Sentiment Classification | 1806.05507 | http://arxiv.org/abs/1806.05507v1 | http://arxiv.org/pdf/1806.05507v1.pdf | https://github.com/rktamplayo/HCSC | true | true | false | tf |
https://paperswithcode.com/paper/a-data-set-of-piercing-needle-through | A data-set of piercing needle through deformable objects for Deep Learning from Demonstrations | 2012.02458 | https://arxiv.org/abs/2012.02458v1 | https://arxiv.org/pdf/2012.02458v1.pdf | https://github.com/imanlab/d-lfd | true | true | true | tf |
https://paperswithcode.com/paper/flexwatts-a-power-and-workload-aware-hybrid | FlexWatts: A Power- and Workload-Aware Hybrid Power Delivery Network for Energy-Efficient Microprocessors | 2009.09094 | http://arxiv.org/abs/2009.09094v1 | http://arxiv.org/pdf/2009.09094v1.pdf | https://github.com/CMU-SAFARI/PDNspot | true | true | false | none |
https://paperswithcode.com/paper/local-variables-and-quantum-relational-hoare | Local Variables and Quantum Relational Hoare Logic | 2007.14155 | http://arxiv.org/abs/2007.14155v1 | http://arxiv.org/pdf/2007.14155v1.pdf | https://github.com/dominique-unruh/qrhl-local-variables-isabelle | true | true | false | none |
https://paperswithcode.com/paper/rethinking-fun-frequency-domain-utilization | Rethinking FUN: Frequency-Domain Utilization Networks | 2012.03357 | https://arxiv.org/abs/2012.03357v1 | https://arxiv.org/pdf/2012.03357v1.pdf | https://github.com/kfir99/FUN | true | true | true | pytorch |
https://paperswithcode.com/paper/selfpose-3d-egocentric-pose-estimation-from-a | SelfPose: 3D Egocentric Pose Estimation from a Headset Mounted Camera | 2011.01519 | https://arxiv.org/abs/2011.01519v1 | https://arxiv.org/pdf/2011.01519v1.pdf | https://github.com/facebookresearch/xR-EgoPose | false | false | false | pytorch |
https://paperswithcode.com/paper/balancing-rational-and-other-regarding | Balancing Rational and Other-Regarding Preferences in Cooperative-Competitive Environments | 2102.12307 | https://arxiv.org/abs/2102.12307v1 | https://arxiv.org/pdf/2102.12307v1.pdf | https://github.com/jbr-ai-labs/BAROCCO | false | true | false | pytorch |
https://paperswithcode.com/paper/one-shot-video-object-segmentation | One-Shot Video Object Segmentation | 1611.05198 | http://arxiv.org/abs/1611.05198v4 | http://arxiv.org/pdf/1611.05198v4.pdf | https://github.com/Mind23-2/MindCode-5/tree/main/OSVOS | false | false | false | mindspore |
https://paperswithcode.com/paper/reducing-network-agnostophobia | Reducing Network Agnostophobia | 1811.04110 | http://arxiv.org/abs/1811.04110v2 | http://arxiv.org/pdf/1811.04110v2.pdf | https://github.com/ROBOTICSENGINEER/Reducing-Network-Agnostophobia-Center-Loss | false | false | false | tf |
https://paperswithcode.com/paper/boundary-topological-entanglement-entropy-in | Boundary topological entanglement entropy in two and three dimensions | 2012.05244 | https://arxiv.org/abs/2012.05244v2 | https://arxiv.org/pdf/2012.05244v2.pdf | https://github.com/JCBridgeman/UnitaryPremodularCategoryData | true | true | false | none |
https://paperswithcode.com/paper/securing-deep-spiking-neural-networks-against | Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters | 2012.05321 | https://arxiv.org/abs/2012.05321v1 | https://arxiv.org/pdf/2012.05321v1.pdf | https://github.com/rda-ela/SNN-Adversarial-Attacks | true | true | true | pytorch |
https://paperswithcode.com/paper/learning-from-an-exploring-demonstrator | Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits | 2106.14866 | https://arxiv.org/abs/2106.14866v2 | https://arxiv.org/pdf/2106.14866v2.pdf | https://github.com/wenshuoguo/inverse-bandit-code-release | true | true | true | none |
https://paperswithcode.com/paper/mali-a-memory-efficient-and-reverse-accurate-1 | MALI: A memory efficient and reverse accurate integrator for Neural ODEs | 2102.04668 | https://arxiv.org/abs/2102.04668v2 | https://arxiv.org/pdf/2102.04668v2.pdf | https://github.com/juntang-zhuang/TorchDiffEqPack | true | true | false | pytorch |
https://paperswithcode.com/paper/direct-design-of-biquad-filter-cascades-with | Direct design of biquad filter cascades with deep learning by sampling random polynomials | 2110.03691 | https://arxiv.org/abs/2110.03691v2 | https://arxiv.org/pdf/2110.03691v2.pdf | https://github.com/csteinmetz1/iirnet | true | true | true | pytorch |
https://paperswithcode.com/paper/woodbury-transformations-for-deep-generative | Woodbury Transformations for Deep Generative Flows | 2002.12229 | https://arxiv.org/abs/2002.12229v3 | https://arxiv.org/pdf/2002.12229v3.pdf | https://github.com/yolu1055/WoodburyTransformations | true | false | true | pytorch |
https://paperswithcode.com/paper/using-inverse-optimization-to-learn-cost | Using Inverse Optimization to Learn Cost Functions in Generalized Nash Games | 2102.12415 | https://arxiv.org/abs/2102.12415v1 | https://arxiv.org/pdf/2102.12415v1.pdf | https://github.com/sallen7/IO_GNEP | true | true | false | none |
https://paperswithcode.com/paper/causal-discovery-with-unobserved-confounding | Causal Discovery with Unobserved Confounding and non-Gaussian Data | 2007.11131 | https://arxiv.org/abs/2007.11131v2 | https://arxiv.org/pdf/2007.11131v2.pdf | https://github.com/ysamwang/ngBap | true | true | false | none |
https://paperswithcode.com/paper/swagan-a-style-based-wavelet-driven | SWAGAN: A Style-based Wavelet-driven Generative Model | 2102.06108 | https://arxiv.org/abs/2102.06108v1 | https://arxiv.org/pdf/2102.06108v1.pdf | https://github.com/dkn16/stylegan2-pytorch | false | false | true | pytorch |
https://paperswithcode.com/paper/rounding-error-using-low-precision | Rounding error using low precision approximate random variables | 2012.09739 | https://arxiv.org/abs/2012.09739v1 | https://arxiv.org/pdf/2012.09739v1.pdf | https://github.com/oliversheridanmethven/low_precision_approximate_random_variables | true | true | false | none |
https://paperswithcode.com/paper/draw-your-neural-networks | Draw your Neural Networks | 2012.09609 | https://arxiv.org/abs/2012.09609v1 | https://arxiv.org/pdf/2012.09609v1.pdf | https://github.com/jatinsha/sketch | true | true | false | pytorch |
https://paperswithcode.com/paper/impact-of-non-normal-error-distributions-on | Impact of non-normal error distributions on the benchmarking and ranking of Quantum Machine Learning models | 2004.02524 | https://arxiv.org/abs/2004.02524v1 | https://arxiv.org/pdf/2004.02524v1.pdf | https://github.com/ppernot/ML2020 | true | false | true | none |
https://paperswithcode.com/paper/analyzing-and-improving-the-image-quality-of | Analyzing and Improving the Image Quality of StyleGAN | 1912.04958 | https://arxiv.org/abs/1912.04958v2 | https://arxiv.org/pdf/1912.04958v2.pdf | https://github.com/dkn16/stylegan2-pytorch | false | false | true | pytorch |
https://paperswithcode.com/paper/training-effective-ensemble-on-imbalanced | Self-paced Ensemble for Highly Imbalanced Massive Data Classification | 1909.03500 | https://arxiv.org/abs/1909.03500v3 | https://arxiv.org/pdf/1909.03500v3.pdf | https://github.com/ZhiningLiu1998/self-paced-ensemble | true | true | true | none |
https://paperswithcode.com/paper/node-feature-extraction-by-self-supervised-1 | Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction | 2111.00064 | https://arxiv.org/abs/2111.00064v3 | https://arxiv.org/pdf/2111.00064v3.pdf | https://github.com/elichienxD/SAGN_with_SLE | false | false | true | pytorch |
https://paperswithcode.com/paper/the-weighted-kendall-and-high-order-kernels | The Weighted Kendall and High-order Kernels for Permutations | 1802.08526 | http://arxiv.org/abs/1802.08526v2 | http://arxiv.org/pdf/1802.08526v2.pdf | https://github.com/YunlongJiao/weightedkendall | true | true | true | none |
https://paperswithcode.com/paper/collision-free-trajectory-optimization-in | Collision-Free Trajectory Optimization in Cluttered Environments Using Sums-of-Squares Programming | 2404.05242 | https://arxiv.org/abs/2404.05242v2 | https://arxiv.org/pdf/2404.05242v2.pdf | https://github.com/lyl00/minimum_scaling_free_region | true | true | true | none |
https://paperswithcode.com/paper/you-only-look-twice-rapid-multi-scale-object | You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery | 1805.09512 | http://arxiv.org/abs/1805.09512v1 | http://arxiv.org/pdf/1805.09512v1.pdf | https://github.com/zk2ly/Glass_insulator_defect_detection | false | false | true | pytorch |
https://paperswithcode.com/paper/chatgpt-for-digital-forensic-investigation | ChatGPT for Digital Forensic Investigation: The Good, The Bad, and The Unknown | 2307.10195 | https://arxiv.org/abs/2307.10195v1 | https://arxiv.org/pdf/2307.10195v1.pdf | https://github.com/markscanlonucd/chatgpt-for-digital-forensics | true | true | false | none |
https://paperswithcode.com/paper/bilinear-representation-for-language-based | Bilinear Representation for Language-based Image Editing Using Conditional Generative Adversarial Networks | 1903.07499 | http://arxiv.org/abs/1903.07499v1 | http://arxiv.org/pdf/1903.07499v1.pdf | https://github.com/vtddggg/BilinearGAN_for_LBIE | true | true | true | pytorch |
https://paperswithcode.com/paper/non-commutative-blahut-arimoto-algorithms | Computing Quantum Channel Capacities | 1905.01286 | https://arxiv.org/abs/1905.01286v4 | https://arxiv.org/pdf/1905.01286v4.pdf | https://github.com/sagnikb/quantum-blahut-arimoto | false | false | true | none |
https://paperswithcode.com/paper/beyond-part-models-person-retrieval-with | Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline) | 1711.09349 | http://arxiv.org/abs/1711.09349v3 | http://arxiv.org/pdf/1711.09349v3.pdf | https://github.com/Mind23-2/MindCode-5/tree/main/pcb_rpp | false | false | false | mindspore |
https://paperswithcode.com/paper/convtransformer-a-convolutional-transformer | ConvTransformer: A Convolutional Transformer Network for Video Frame Synthesis | 2011.10185 | https://arxiv.org/abs/2011.10185v2 | https://arxiv.org/pdf/2011.10185v2.pdf | https://github.com/harryzhu123/ConvTransformer | false | false | true | pytorch |
https://paperswithcode.com/paper/decoupling-semantic-context-and-color | Decoupling Semantic Context and Color Correlation with multi-class cross branch regularization | 1810.07901 | http://arxiv.org/abs/1810.07901v2 | http://arxiv.org/pdf/1810.07901v2.pdf | https://github.com/tejgvsl/Color-constancy | true | false | false | tf |
https://paperswithcode.com/paper/visual-transformers-token-based-image | Visual Transformers: Token-based Image Representation and Processing for Computer Vision | 2006.03677 | https://arxiv.org/abs/2006.03677v4 | https://arxiv.org/pdf/2006.03677v4.pdf | https://github.com/aws-samples/amazon-sagemaker-visual-transformer | false | false | true | pytorch |
https://paperswithcode.com/paper/learning-by-fixing-solving-math-word-problems | Learning by Fixing: Solving Math Word Problems with Weak Supervision | 2012.10582 | https://arxiv.org/abs/2012.10582v2 | https://arxiv.org/pdf/2012.10582v2.pdf | https://github.com/evelinehong/LBF | true | false | true | pytorch |
https://paperswithcode.com/paper/deep-co-attention-network-for-multi-view | Deep Co-Attention Network for Multi-View Subspace Learning | 2102.07751 | https://arxiv.org/abs/2102.07751v1 | https://arxiv.org/pdf/2102.07751v1.pdf | https://github.com/Leo02016/ANTS | true | true | false | pytorch |
https://paperswithcode.com/paper/bridging-textual-and-tabular-data-for-cross | Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing | 2012.12627 | https://arxiv.org/abs/2012.12627v2 | https://arxiv.org/pdf/2012.12627v2.pdf | https://github.com/salesforce/TabularSemanticParsing | true | true | true | pytorch |
https://paperswithcode.com/paper/autoprof-i-an-automated-non-parametric-light | AutoProf -- I. An automated non-parametric light profile pipeline for modern galaxy surveys | 2106.13809 | https://arxiv.org/abs/2106.13809v2 | https://arxiv.org/pdf/2106.13809v2.pdf | https://github.com/ConnorStoneAstro/AutoProf | true | true | false | pytorch |
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