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A promising direction that could allow us to make progress with computing the inner product measure is rooted in the BKL conjecture, which states that as one approaches a space-like singularity, spatial derivatives become negligible {{cite:da778f700dec2a4b7e4a5aa7217ea625f38c6471}}. In the context of the Kodama state, ... | d | 60df26057fd7ea4bdaeed549978814ee |
Along with the success of unsupervised pretraining applied in deep learning, others are studying unsupervised learning algorithms for generative models, such as Deep Belief Networks (DBN) and Denoised Auto-encoders (DA) {{cite:90e6789a0faa30851a2d9d3609ce82ff709cef44}}, {{cite:845504b2ee11a6b81ce998413fc49dcb4d008338}}... | i | 9f993b0f993dc3510d4758c0fea8bf53 |
When a vessel containing a liquid is subjected to vertical oscillation, nonlinear standing waves form on the liquid interface, which were first reported by Michael Faraday {{cite:c32d00a1655afc2e3611f69b21f74c36e397c460}} and are called "Faraday Waves" after him. Many studies have been performed on Faraday waves, inves... | i | 9bad4622a357c707a23364fd4bcaafef |
In this work we focus on evaluating the expected information gain (EIG), a commonly used utility function in Bayesian optimal experiment design (BOED) {{cite:19f25a224d3b13f190a26cd2e3b5ce380b8aee9d}}, {{cite:6483c497464ea6db7adf3b18d7aee2edcc349947}}. We specify our model, composed of a likelihood and prior {{formula:... | i | 967446855a515fca5a94fbc6e91d7b30 |
As the average probability {{formula:42a051cb-3181-4836-8ce8-055dac272006}} of {{formula:c1709cca-9da7-4665-a3fa-b7dd7ca64a28}} and 10 shown in Fig. REF , REF and REF , we can clearly see that as {{formula:3747bc0a-754c-407d-ad37-bbadd948dd5d}} increases, the transition is becoming increasingly abrupt near the crit... | r | 14767acbc2b13843e483a8dbe42abb52 |
water,
resulting in an aggregate degree of child poverty between 0 and 7 with 0 indicating no poverty and 7 indicating severe poverty.
Due to the sensitive nature and the accompanying ethical considerations, the IMF dataset is not made publicly available and can be requested upon from the original authors of {{cite:02... | r | e7e46713256c769d29f06575e0d31aa6 |
A wide range of important work actually trust SentEval {{cite:c277b4da6d500760f81885eaee94e0732dfb7dd8}}, {{cite:bd9b917a2245d4300e262f56809fbef4a72df821}}, {{cite:f82caca027112bc8cbf15a85afd1431c55c27f18}}, {{cite:f4ede6475a6dc6a815b1bbc3ae7ed04974e9d418}} or GLUE {{cite:6c41f38aa1aaee6ef91316464da69e9766a75eb0}} in o... | i | 92c09138c2e6664737a59d26948db700 |
The exponent {{formula:4c43b32d-668f-43dc-90de-7f22ea81ab9d}} = 0.6 is close to 1/{{formula:056ae0b8-1e4e-4c06-9563-90f1698305ad}} for the non-degenerate Fermi gas with {{formula:04943348-83de-4d8b-8ac1-9ffa5381adb5}} {{cite:9e95cba56c223465a2f200211fc0c206a753cd0a}}, {{cite:914ad666f435caed49bde884bce62f87e545d514}... | d | dd264213ea240087ce17c223be9d9272 |
Multimodal methods. We evaluate two varieties of multimodal models: i) unimodal pretrained and ii) multimodal pretrained. In the unimodal pretrained category we explore MMBT {{cite:e8432eaddbf63656eebcc6abadbdd7f9f1104aae}}, MoViE+MCAN {{cite:4e3f090a27f5ef2b26edcaae217f3154ee82e158}} and UniT {{cite:30ced543abd79a1988... | m | a95a3454b07cea543aa4b0a0b1d203f8 |
Semantic label to face generation. The quantitative results for semantic face generation on the FFHQ and CelebA datasets can be found in Tables REF and REF , respectively.
As the choice of comparison methods, we use the current state-of-the-art method for semantic face generation TediGAN {{cite:c5c85813ed1a15ee76eff60... | d | 380eba1f635a3ec39a68c76d9f713bc0 |
Finally, we return to the question of whether rotating the applied field away from the {{formula:f953aca5-77df-4713-8198-cf752d43456f}} axis will break the VL domain degeneracy within the L phase.
Such an effect was previously observed in TmNi{{formula:8149724b-8b21-4597-928a-265c1b598802}} B{{formula:514323dc-a462-49... | d | f8d2d9dae7efe88981c1e50ef7229013 |
The policy is trained with a Huber loss ({{formula:5c0fa57c-d9e1-4b01-a7d5-3a1feccf2509}} ), that in practice is usually just an MSE loss, since predictions almost always lie within {{formula:a6dceb0d-223d-4711-8684-e4b87de8d6a1}} . A deterministic policy trained with mean-squared error can be viewed as max likelihood... | r | 52e1c9920a57dc17ece51b0052ae62c1 |
The mean average precision (mAP) results comparing with state-of-the-art methods are shown in Table REF . The CNNH {{cite:dec23ffe2d8651ace04f4b511ee02c5d10503af1}}, DNNH {{cite:97d96dc337f2fb92ccbb07bd1ce7efa89bcd8a04}}, DHN {{cite:3903a399de76c85f164bc7bbfbdb4d13770aaac1}}, HashNet {{cite:369551173cc8ce173f976ed49127... | m | 3d9d9cf06cf4f6c1e7e2be28544dc2d5 |
(i) Root Count: Consider the example system (taken from {{cite:c6866f42917230a7560cabb0c61293c80d46cc85}}) with two unknown variables {{formula:591fca45-55e5-49f1-8cc9-1c55e18d5ed7}} and with 4 solutions.
{{formula:81e7ab21-affe-4f3e-8ebe-8cf25b6d90c5}}
| m | f90b4eb992378395c3bcbb923e4a99f0 |
Nonetheless, there are several directions towards which our results may be improved which we aim at investigating in the future. First, future work will be devoted to adding explicit dynamic reasoning withing the neural network, for example by introducing recurrent layers {{cite:e28546d4101bb570cde5e3045f5490cc031524e7... | d | 05a22863b015ebfe96d56535c98d0c64 |
Differential rotation on tides should also be taken into account, as it
affects propagation of gravito-inertial waves, leading to a large variety of resonant cavities as well as chaotic zones {{cite:fe33520fff5f005a93664c8fd4df80a41f0f96cf}}, {{cite:c7093aba620cb4822bdd6a672627904a38853dd3}}. It also allows the deposit... | d | f0dde0b5f504226170b4d821bf131d86 |
In Fig. REF the mean and standard deviation of the {{formula:7aee4d84-45ce-4eb6-a611-1bf979f79129}} spectra are compared for pp, p==Pb and Pb==Pb collisions at the same centre-of-mass energy per nucleon pair of {{formula:14a2ff9d-2f3e-401d-a06d-4ec7344230ab}} .
All three collision systems have similar values at {{for... | r | fb4922a3b15b1b86203186416b9ace5c |
The inception of deep neural networks has revolutionized the landscape of medical image segmentation {{cite:527f6cdbce3e32f393c5005c8f6a4fe58ef682d0}}, {{cite:d66c24202c59ad47130ef335a6f8ac909badb028}}, {{cite:59b4b56ed873d7a1e9053c28136b99892db10626}}. Despite their tremendous success, however, depriving them of suffi... | i | 493a3407e5b2f3b559667721d81b772a |
+ Cutout {{cite:2d3adb4be9993263cd366c1e24bdd5918ac98efc}} - - - {{formula:1dab5b94-5507-4b01-b366-869c51762ff1}}
| r | fcafdbdea5fd071fa8866034c7307093 |
There is widespread agreement that there are limitations to network generalization {{cite:90ab722e02caf2e33ea1ced8cc54a59da7f1c282}}. There is also consensus that modern artificial networks do not generalize as well or in the same way as humans {{cite:a841b3e0ed6bcd5a588253bd1567d1375f2666fb}}. There are conflicting vi... | d | 9c307376850716940b2d0891c79aaba3 |
Neural-network image classifiers are well-known to be susceptible to adversarial examples—images that are perturbed in a way that is largely imperceptable to humans but that cause the neural network to make misclassifications. Much research has gone into methods for constructing adverarial examples in order to understa... | i | 3628f60e20c62384c3d17ba2107141f6 |
The strong interaction in a fully heavy multiquark state is not clear at present. The Chromomagnetic Interaction (CMI) model provides us a simply picture to quantitatively understand the spectrum of multiquark states. In the framework of CMI model {{cite:7f24989299b7a49302980c76bc6e2d336886e467}}, the strong interactio... | i | 9837ff53f018c0f2a8a6bfdeb25c984f |
Note that our problem formulation is same as that of existing works
with the distinction that we replace the requirement of a large-scale
corpus by the availability of pre-trained word embeddings. This makes
our setting more appealing and flexible, as pre-trained embeddings
are widely available (e.g., word2vec, Glove, ... | i | 383aa54556ded0d3a71d0cfc59b5bb54 |
We compare our method with DENet {{cite:0ac20a8d8c59848da79c2a710fb07e893e0becdc}}, CAPL {{cite:d02424dba819075252059625b5795ba848f01ec2}}, PFENet {{cite:1e0107c7bbf058c7521836a384e75a054464aa7e}} and ACASTLE {{cite:ccb7fcc643f1684a3b9f3d31554e000962db7142}}.
DENet and CAPL are two state-of-the-art GFSS methods. PFENet... | m | 44a0b240aabe97f0b2424aabe377c987 |
Previous research on supporting user goals on the web has primarily sought to understand and categorize a person's intent manifested through search queries.
In their seminal studies, {{cite:a14f08f2ae02c2c0af277ae2eb2871afc5de6efc}} and {{cite:5576e6849bb27ae5be46fa91beceaa3506c53c55}} classified the goal of a user que... | i | 79470c87d446d4403aad37f8e8645932 |
We used a rather general approach to analytical
evaluation of the 2-point and 4-point zig-zag diagrams.
This approach leads to a fairly simple
proof of the Broadhurst-Kreimer conjecture
that is different from the proof of {{cite:a9d48067d1f4e0c43f73c221e59a0285e042a99e}}. Here
we make use the operator formalism {{cite:... | i | 1ae80d28b9faa87b433fde062758c301 |
The symmetric Lanczos {{cite:8754e9dd06eb0682a56f4455b4b7995b98b05c2b}} and the GK algorithms are closely related: indeed,
multiplying the first expression in (REF ) from the left by {{formula:40d5dd52-fc42-4b2a-a38e-9bdda15ec7b5}} , and using again the second equation in (REF ), one obtains
{{formula:10047f45-4a83-4f9... | m | c5080888e076aa5fc20fa5a7a72be12a |
Application to Performance estimation problems (PEPs). PEPs were introduced by {{cite:840c49cfabee540c8ab2ec8e3177a734d94b7c2b}} for developing new analyses of first-order methods; see also {{cite:18bd9b6e419785a8e2c04194f61ce016a0010bb1}}, {{cite:84e9e87af300271ea2f40a2517f0085757859fa4}} for the first works on this t... | r | f2db8f14db466f8aaa5fb74cc555165a |
A matrix with real number entries is said to be totally nonnegative if each of its minors is nonnegative. Totally nonnegative matrices arise in many different settings, for example, oscillations in mechanical
systems, stochastic processes and approximation theory, Pólya frequency sequences,
representation theory, plana... | r | a06bf6d9cb04f5989118dc0161a46429 |
To investigate if early warning signals are vulnerable to this fallacy,
we simulate a system that is not driven towards a bifurcation such as
in Fig reffig:1(b). This simulation approach allows us to determine whether
examining historical events is a valid way to test the utility of these
indicators. We simulated 20,00... | m | 698acfb3b0f701994b6b07bec4bc7965 |
We want to evaluate if our method qualitatively improves upon ILO {{cite:072aa8697aa30c37d7c522369c02c42c45ce5021}} which is the previous state-of-the-art method for solving inverse problems with pre-trained generators. We also compare with vanilla CSGM {{cite:5ae1771503323a77674c2adec5430e777a755377}} which performs m... | r | 3f718ba3c487f6037b178b1c13417aa5 |
The special case {{formula:676a3110-e92b-4f52-a465-aefa739d9945}} corresponds to the ultraspherical or Gegenbauer polynomials {{formula:f64b29ed-2ea4-4dd4-8315-7c5b3cac85a8}} with slightly different normalization, and the case {{formula:7bece5eb-7778-4e33-8484-da362b1e6eb5}} corresponds to the Legendre polynomials (... | i | b5fde6f1f67df9f22134f6aacf230d3b |
Based on the impact parameter analysis of Swift bursts, the corresponding volumetric rate density is {{formula:0e4f11b2-b94c-4116-877a-4ece41215bf9}} {{formula:09ad4aed-d62b-46fb-bdd8-d6566ec2ffe5}} . This falls below the {{formula:ea6eb8bd-ad87-400b-9671-ae03399e62cb}} range estimated for NSNS mergers by {{cite:0ab9... | d | a95d8d701dae53fb2b8bdecc7910668f |
With other parametrizations, relative contributions of horizon and dark
energy entropy decide the evolution of total entropy. The signs of {{formula:8dfc6ff5-c561-461b-9fd0-d541275cd0bb}} and {{formula:557f603d-24d4-4e0e-b6df-10f9016060f7}} are
decided by the terms ({{formula:3eca5dc8-0fbc-4103-a40c-765aef268e92}} ) ... | r | 935839d836795470a2cbcf1ce8463705 |
It is hard to exaggerate the importance that fairness has now taken within Machine Learning (ML) {{cite:c3056bc66f0f48c9781734b234e3f6bfe0653c2d}}, {{cite:048133cc7e6e32fb1eb182b6bc4601dab50af504}}, {{cite:2d716777e06ea21e40ea232303a73072f9ff9e3a}} (and references therein). ML being a data processing field, a common up... | i | 6e60d3a6a28b98a1099d675832b8a7d2 |
Several theoretical methods have been developed for the global polarization.
These theoretical methods can be roughly put into three categories.
One category is related to the quantum statistical theory for particle
systems with spin degrees of freedom in equilibrium {{cite:ea83158f3f694d0c159b4639e753519d59ca8b45}}, {... | i | 04ab31bf6c599ea2f23bd4a4734db388 |
Throughout this paper, we use the 2018 cosmology as our fiducial cosmology. We take the values given in Table 2, in the column 6 (best-fit with BAO), of {{cite:faf2a6b748ad7fad05a12ab8d0581c68c2d3e3e2}}.
We use the following naming conventions: observable refers to a spherical 2D field built on measured quantities, suc... | i | 370560535d799e4dd7335dcc9c4ddfd1 |
Integrated Gradients. Gradient explanations are often noisy and suffer from saturation problems {{cite:4bc83980c609b5b14243c852df077e39cab9b97b}}. Integrated gradients addresses the gradient saturation problem by averaging the gradients over a set of interpolated inputs derived using node {{formula:f0693d8f-1a04-4687-b... | m | 0824bfc719b8ed9fdb9049c258f4adc3 |
LOCCNet not only unifies and extends the existing LOCC protocols, but also sheds light on the power and limitation of LOCC in the noisy intermediate-scale quantum (NISQ) era {{cite:c9c81b2e460c8591e714120a53d5a123207cc822}} by providing a plethora of examples. We developed improved protocols for entanglement distillati... | d | 91d35a82bd76afc823352625cd98bda6 |
In real-world situations, running randomized controlled trials uncovering causal relationships for BN can be costly and time consuming. Sometimes, it is even impossible due to ethical concerns. Thus, it has been of great interest to develop statistical methods to infer the structure of BN purely based on observed data.... | i | e2459e8755b4b52eb390ebb1a34f4317 |
Remark 1.2 In the development of this article, we learned that the authors of {{cite:953d04ea12e60a92854f285f9bcb9aef33e5bb5e}} were also studying holomorphic symplectic structures on augmentation varieties, working on a different construction with plabic graphs. Their work is yet to appear but, once it does, it would ... | r | da0f1464ea8ec9d60b1f11fceb3cb456 |
Although several algorithms exist for training NN models, the backpropagation algorithm {{cite:3d156d0b060d7284f270fd0d01397d33411cd24a}}, {{cite:f535d01efd639ce974f4f4a6d27f9a512958bfd5}} with stochastic gradient descent (or variants thereof {{cite:caa4991ba1a5fcb0da153be83b876d03e0bf0185}}) has been established as a ... | i | e63986bc872f251ac776933373bca682 |
In addition to the results shown above, we also present qualitative correspondence results between neural implicit fields and real-world data in the supplementary. More specifically, in Section 5 of the supplementary, we show qualitative interpolation and correspondence results between implicitly defined surfaces. Then... | r | 521537ba45671b0454b0a0d048e23365 |
Inspired by recent research {{cite:8fac9444d4996db26fa03ae7a0ed7851a52234dd}}, {{cite:884275d1bdf4f97550a99748b4d8840a116053f7}}, in this paper we present an optimal control and inverse optimal control based method for interactive motion planning in automated driving highway merging. Our method not only incorporates th... | i | 5371d454ef3f0d52e500ce8a139f228f |
Several prior studies have considered the role of directionality in population structure on the spread of mutant types {{cite:ca73af6ffa4b9973a4897e81af851c4cd1f28919}}, {{cite:e72ea306afb4516465b08e354c038f6a38c14908}}, {{cite:fcb6d437d9bfd69569d3f56d726f3073d2ed1dab}}, {{cite:f76fd9c39fbc8bdd4141ebcba0d83bb1badb1d22}... | d | 46a0088c52960a0bf29d511e240b65a5 |
There are situations, however, when even higher-order numerical approximations ({{formula:209b74da-7e0b-49c7-bdc4-a2dd9ce1281c}} ) are
required, for instance in problems arising in astrodynamics. In that case, although generic splitting methods exist, they involve such a large number
of elementary flows {{formula:e5c34... | i | 3cb0029287f91ec5ef7991f325cf2337 |
We in no way claim that CHAMP resolves all of the problems with modularity-based methods(see, e.g., the discussion in {{cite:2fae793edf0531a7f8a1a69f58b38bc8a6f5df93}}). And CHAMP is certainly not the only way to try to process different results across various resolution parameters (see again the Introduction). However... | d | 8ec6ebc095e32c24f3c25b1841bdb685 |
Theorem 9 (Hoeffding Bound, {{cite:365b7a9e1c224b2448fab3798e54a79d09affdf3}})
Let {{formula:dcd8a853-9a39-4c94-852c-7630bef0e651}} be independent random variables. Assume {{formula:a9194299-7aa1-47a9-9eb9-b23445025639}} has mean {{formula:999d0bd9-13e5-4a26-8c12-33a20cfbe493}} and sub-Gaussian parameter {{formula:... | r | 810f943b221ea3a2f358465c97d8c6e4 |
Though the focus has been on the applications of fluid dynamics
near local equilibrium of the system by using the gradient expansion,
it is important to explore whether the applicability can also be
extended to fluid dynamics far from local equilibrium
{{cite:ecbb1fb679601c84f0a5b83eb22f77e9dd604152}}.
This issue has o... | d | 4943c0761298b8d796d695a90350497c |
The code employed for this article, ASDG, can identify the connection between a paper and an SDG through its abstract. It uses four different models: Non-Negative Matrix Factorization (NMF) {{cite:d959994775a133fe0bbffb76ac6585fa942beb0a}}, Distributed Representations of Topics (Top2Vec) {{cite:3187b4aa355393aa5c98dcd4... | m | e50c0341427220b5cf61199ab94f33f7 |
Whole Heart Segmentation Dataset {{cite:81391d65998dec5833144bb471384f81af5d4a48}}. In total, this dataset provided 120 multi-modality whole heart images from multiple sites, including 60 cardiac CT. We selected the CT images and split 20 images to form the training set, and the remaining 40 to form the test set. We pa... | r | 76e3f4373dd3ccbeead65c65f9ad8e60 |
A consequence of the above scenario for water formation is that the D/H ratio of water could depend on the physical conditions in the molecular cloud and prestellar core prior to and during the protostellar collapse. Lower temperatures or a longer duration of the deeply embedded phase would increase the D/H ratio obser... | i | 3eafe04e3455cb70ced215c2d527e8bf |
In the distributed optimization problems mentioned above, the agents decide the same variable while need to reach consensus on the optimal decision. However, in other scenarios, each agent only decides its own variable but the objective function of each agent is related to other agents' decisions through an aggregated ... | i | 7df3ba30429a1e87353407c2cb467fe2 |
(i)
How to directly analyze for {{formula:02124a21-d1b1-46a7-8c75-ebc51c00831d}} in Section ? In this case, main difficulties have been described in Remark REF .
Besides, after opening lens, we have to deal with the singularities at {{formula:995002ab-c0bb-45f9-b35e-a6faccb1293b}} under the second jump factorization... | d | 6c6e38d7471c43a1b4d41bf0ee4c7fb8 |
Where {{formula:1d338bd3-185e-49e2-8943-25a4262e78f6}} is the sigmoid function and K is number of negative samples, typically 5, and {{formula:25938c58-d9b1-4b53-ad61-19d0c8ebcf8e}} is a probability distribution over {{formula:d12b9250-7aec-4ffc-a623-ac6acada56ac}} . It is often based on the degree of {{formula:4ed4d... | m | 015b3868f98e9cec28b67515b01e02ca |
To demonstrate the effectiveness of the suggested method, we train all classifiers using the standard cross-entropy loss and our modified loss and compare post-hoc OOD detection methods across three NAS datasets.
Specifically, we present the results of the confidence-based (i.e., MSP and ODIN) and the distance-based me... | r | e86baeeb84bd5283456c0225932fa12b |
While research on noise robust methods for single-label classification is well established in the CV community, with consistent definitions of label noise and benchmark datasets, most research conducted in the multi-label case appears to be more heterogeneous. Some research fields treat multi-label noise partially, wit... | m | 39c67cb7b682519855afce535a8a694d |
A second ingredient to the distinct behavior of positive and negative disclinations is the asymmetric dependence of conformal crystal structure on the sign of topological charge. As described in Sec. REF , disclinations act monopole sources for conformal distortions of {{formula:c4d082c0-32ee-4543-a32b-13e49897772c}} ,... | d | f784e7c09ca5e45120831e4d1a0eb576 |
By studying the three-body hadronic {{formula:fe7619d4-7397-47af-b3cd-f3dbaf21c2be}} meson decays involving {{formula:6d50355a-6479-4081-b604-0e58986c280b}} , one could provide the constraint on the unitary
triangle {{cite:2fc8efa20cdd89b6d39498f9381aa4135c8ed88e}}, {{cite:5db5906cd3a417c039d993a4222f3fc59be3fac6}}, {... | i | 53b61ee272503a63d666bf78bbe5098f |
Transferability with regards to machine learning technique: Transferability of adversarial samples {{cite:eee2e77b6d1d5a5aceaa626df20dc1abb6526754}} {{cite:d3c05bf5fd641cddb51c68eb594f3e329ac73fe7}} has been shown to be more effective with targeted adversarial samples {{cite:54469159e35938949297c4540298d39efaa17c7f}}. ... | d | 75303d10b74744efc37477751c37cc86 |
A multilayer approach has been recently suggested to offer a better description of various real-world networks {{cite:27daab30bef2a2e2b0c695f5ef0b63e7efd7d057}}, {{cite:8e9689745c506e1f33dea1eca917fb05c039a677}}, {{cite:ba00a6a2ba59839e9aaec7c76ebfdfeeeb578161}}.
In multilayer networks the nodes are distributed in diff... | i | 4f918841dbac36677ea558648b38ca3d |
We perform a global analysis of all the observables discussed in Section within a Bayesian framework, using the publicly available HEPfit package {{cite:d1642fab88b841ae996ae9aca1f91e50eeaeca4e}}, whose Markov Chain Monte Carlo determination of posteriors is powered by the Bayesian Analysis Toolkit (BAT) {{cite:23b19e... | r | c4eb8c0e8e35c4ae6fefc3e74684495c |
To address this problem, we propose our framework,
Alignment-Aware Acoustic-Text Pretraining
(A{{formula:ef93d5db-d83a-4ec3-83ca-c142770f538a}} T),
where we introduce cross-modal alignment embeddings
which make the model easier to learn the alignment between
the acoustic and phoneme
input during multi-modal pretraining... | i | c9acd29ec3e9b58857d339ca851e82ee |
An important future direction is to study how quantum advantage becomes evident when we replace classical algorithms leveraging the powerful SQ access with measurement data access.
It is likely that various learning tasks considered to have no exponential quantum advantage are thought of as such due to the power of SQ ... | d | 57f96015e6892a0fcea457a33fdfa04c |
Testing this hypothesis proves to be a formidable task for the present possibilities. The same mechanism underlying the flavor vacuum condensation is responsible for QFT modifications to the neutrino oscillation formulas. Yet these modifications are mostly negligible except for non-relativistc neutrinos {{formula:9bc88... | i | ffa6dbb21dbc2d84522f99b83afc5afa |
Remark: Concurrently and independently from this paper, {{cite:f72a1881b2367d1118cba541c8b67e03878a9840}} recently achieved a parallel algorithm with {{formula:1003fab4-152c-4d06-b249-76635f86786d}} depth and {{formula:c6308ebc-e43b-4f41-ad68-0d61de4a8451}} work by parallelizing the sequential algorithm of {{cite:ed1... | r | 41afb5c798059c6fe777e97263105093 |
With Assumption REF on {{formula:cc6a0f39-1fa7-4b64-bfe6-d9c2e92968ac}} -smoothness and {{formula:1a975854-e53a-448d-a4bf-3bf75b9ead40}} -strong convexity of {{formula:9a55fdb3-de18-4323-b03e-ee4d334e7f81}} , according to {{cite:2248992355268d1a65c9aafaec42c0c13c60c410}}[Theorems 2.1.5, 2.1.10, and 2.1.12], we have th... | r | 06ecc79c304798f06ca492df4f4bbb04 |
The experimental setup is inspired by the one proposed in {{formula:9faf5955-0e3d-4ad3-8309-d147cbf39278}} {{cite:972453db4295fc785ee30b269efdc72b1956ab13}}.
Each dataset of 1000 classes is split into {{formula:500a9207-881a-4ffa-a214-eefd209fa018}} incremental states.
Each incremental state adds a batch of {{formula... | m | 37208e629982f9529943012152c2611c |
If we use the amplitude amplification procedure {{cite:a260b21cbc0831fdab60dad07fcac6dcecc6f672}}, the time complexity of the search algorithm is {{formula:1cfa0717-3fea-4a46-a87e-4fcd8f159f47}} . Using Eqs. (REF ) and (REF ), the total running time with success probability {{formula:d73c0eae-61c5-4025-8562-34f51762287... | m | 6ae21b9a4b6a38f6b3a30553c0bca2de |
We use the fermion mass ratios, mixing angles and CP violation phases to construct the {{formula:81ce405e-400e-4641-afd7-42025712e868}} function, the experimental data of the leptons and quarks are summarized in table REF .
The data of the lepton mixing parameters are taken from the latest global fit of NuFIT v5.0 inc... | r | 4e38eaab9beaec2b396dca40319a2d67 |
The physics of monolayer
transition-metal dichalcogenide (TMD) semiconductors, such as MoSe{{formula:b696f893-fdf2-48c8-b43f-22ce3c443563}} , has has been widely investigated.
Review articles include Refs. wang-etal.12,schaibley-etal.16,choi-etal.16,manzeli-etal.17,berkelbach-reichman.18,mueller-malic.2018.
Examples of... | i | da2c94d157562b66e5e99db47a6e6215 |
We compare the error exponent {{formula:b0c67567-fdb8-41ef-a7ef-f3e3a92decb0}} given in Theorem REF corresponding to list decoding with list size {{formula:ab48dfd5-7c48-4812-82eb-1061e5965e64}} for the random matrix ensemble {{formula:352302f1-575d-473d-8226-214ae873e619}} with {{formula:6669d0e1-9375-4063-9dde-bd... | d | ba27d4e57e21c527a6137fdf0c8e8ede |
We remark that finding {{formula:149e4f26-4036-40df-8878-162cd4a42d6e}} and {{formula:6f44b6c6-ccc3-49c4-b2ae-35d53ddfbd61}} in unambiguously discriminating separable quantum states can be useful in studying the phenomenon of nonlocality without entanglement(NLWE){{cite:cac2056f7201698ac189ee6755daeb51f89bafc4}}.
For... | d | 0c090b912497b365dc351a8c6e5bc59d |
and we also consider {{formula:8aad1ce4-a4d0-4881-93a2-acc6cba84e6f}} that involves derivatives up to {{formula:0bbbab57-3e78-4882-a6c2-b56b26c861ce}} order for a positive integer {{formula:f8ef3e90-09a8-453f-a214-49cd69232d67}} .
There is a reason that we consider only derivatives in the {{formula:5c53ba37-c0f9-42ce... | i | 6121689548cf306aaf0f7a92b8d2dec5 |
where {{formula:f1a1d15a-0760-4374-a9eb-5b23ac7e49f4}} are the eigenfunctions of {{formula:586b9478-8a7a-4dce-9beb-1082978a17ad}} ,
{{formula:64410d4c-d910-4a5d-b205-361ebf47c160}} are the eigenvalues of the corresponding
Floquet Hamiltonian, and the last equation follows from Eq. REF . This procedure thus allows acc... | m | b7b87e31abeb4a417c2943b20634287c |
which avoids singularities as the denominator in Eq. (REF ) is strictly positive for {{formula:bf7de4af-6fb4-47cf-9941-5d628ba2d271}} .
The implementation of Eq. on commonly used learning packages with auto-differentiable features, such as Pytorch {{cite:1ba9b4d9426033bf9ed9244a94e3bc5b7c2490c8}} or JAX {{cite:aacf1b... | m | 54385d89c9212c9c0a062a25c3eb0477 |
A prevailing method to improve the model robustness against adversarial attacks is adversarial training {{cite:1e6622228b3208b486ed8c4da0b3e9dfb571140d}}. In adversarial training, each batch of data is augmented by adding corresponding adversarial examples of the same batch.
In NLP, adversarial training in the input sp... | i | f40135acaacaf826a18b901acae97a11 |
Theorem 2.1 ({{cite:19878d8cbfe36e475fa4ef2ab500e6a12e3bcc49}}, page 344)
For {{formula:6ce1319d-0751-475e-a268-a405a4aae510}} , let {{formula:d7b1edee-9dd7-462b-a89f-99fc008b1ace}} , {{formula:0c7cc9c9-d085-4dce-9556-690688281164}} and {{formula:799e956d-23ed-4e09-bf70-34e6e90b8a99}} . Then the problem
{{formula:67... | r | 3e9fbb2289fd7eef3206bf338bf1a84a |
Moment restrictions identify a parameter of interest by restricting the expectation value of so-called moment functions, which depend on the parameter and random variables representing the underlying noisy data generating process. Important problems in causal inference, economics, and generally robust machine learning ... | i | b90050842c478d573ef846e7a5398f52 |
However, it is not surprising that the CME is significantly more efficient for the amplification of PMFs than in the case of the axion interaction with magnetic fields. In the induction Eq. (REF ), the helicity parameter {{formula:20d00020-7df6-4251-bae6-cf057cd303ce}} , that enters there the PMF instability term {{for... | d | 27d7ff8b37f6c14939105690e8664231 |
Considering that learning the end-to-end translation between RLRD to HRD from unpaired LR-HR data is challenging, part of the one-stage domain translation-based RSISR methods {{cite:d0af3cae52387dc0a9c78e3d19b7ec5271307160}}, {{cite:61ee6d56c1d430878809f1333b5ade4550c223dd}}, {{cite:a9e78c9013e27b9384102770246bd3b31414... | m | b771fd95e3ab7ce80efe8efd2b0979e8 |
For the purpose of our study, we computed the power-law integrated sensitivity curve {{formula:f2097695-e368-41fc-905d-8bdf94a71a72}} , starting from the noise spectral density in {{cite:2a36945450ab95ecc974dede08df53e7098b2d9e}} for ET, {{cite:778c4232132b0095401d77dd57696d87b4cee208}} for CE and {{cite:18c00ec3693d6f... | r | 6a0867d123da88fb7f812099bc1c9cba |
Bayesian networks {{cite:a15e40a0a71a05854a62752b2f601435159b5865}} are a popular framework of choice for representing uncertainty about the world in multiple scientific domains, including medical diagnosis {{cite:63ffa17adb578fc7668e07e09ac3f86b4d25be2f}}, {{cite:e08e962731fbf71244062800acbceae5317425ef}}, molecular b... | i | 3a2c5b5cf2b200e58accbcd709bfbd29 |
for some probability kernel {{formula:049e4463-2af1-4a02-ade8-a85273b3490d}} . Here {{formula:5dc3667d-812b-4ce1-b95d-837a26c6a97c}} acts as mixing distribution and {{formula:cd0dac8b-2bf8-4092-8e04-f7461af2a4a7}} represents the random number of mixture components, thus providing a flexible way to model unobserved he... | i | 170e8d11b77ce90a6b4e5bfd35c6ed71 |
Jelinek-Mercer and Dirichlet prior are the two most common types of smoothing for MNB models. One view
of smoothing is that smoothing methods discount seen occurrences of words in order to redistribute the subtracted
probability mass {{formula:361b918e-05fc-4eeb-9021-912726dec1f5}} to the background model. Under this ... | m | 0deee987263b831ab92d6521a9319755 |
We also show a denoising example based on the “ROF” method (which
consists simply in minimizing the total variation (defined
by the surface tension {{formula:5efdc71d-ec4c-417c-b0ec-58d34dc9ad33}} ) of an image with a quadratic
penalization of the distance to a noisy data, in order to produce a
denoised version, see {{... | r | 7977735ba78d9d2bc59f4a3647887bf3 |
Recently, value-based methods have been applied to multi-agent scenarios to solve complex Markov games and have achieved significant algorithmic progress. VDN {{cite:7b44534cabff9626e2f3da659c317f1ff4456d5b}} represents the joint action-value as a summation of individual value functions. Due to its poor expression fact... | m | 3f0abcaf33992e90a9fda8e84ab41bad |
Given the significant computational effort needed to generate a
network, we propose a strategy that limits the amount of such
generation steps. While it is common in evolutionary algorithms to use
large populations to prevent local minima, this is not the only
possible strategy {{cite:e47d4cd3028cd8e2b24ae31612b074faf1... | m | 425b1b16a4ff106d84f7c329c8eec6ee |
HOCH{{formula:819a9f77-2e7d-46a1-9492-6202561e2a26}} CN is thus far only detected in two sources, SMM1-a and IRAS 16293B {{cite:52bf3ae49d3fb3e8597b4faaf2fe6e357e72caa4}}, and therefore a chemical comparison is limited to these two objects. To use molecular ratios that are unbiased by observational parameters, only dat... | d | e9feb96e42a24febe7111e89e4698dcb |
The vast majority of published video compression research papers provide results using the objective metrics Peak signal-to-noise ratio (PSNR) {{cite:55bd64e0ecf0bba6338e8e25dc150d1e3dbf084c}}, structural similarity index measure (SSIM) {{cite:9aa3c6b7cc661daf95d311b5ef0974caffdf4bb0}}, multi-scale SSIM (MS-SSIM) {{cit... | i | 7c34a6d97752eaa48d881403fdada593 |
For more details about the loss and optimization procedure see {{cite:282c4e00848f5c7a2764b1edc1ea9c5c079d0ef5}}.
Our agent implementation instantiates the policy via {{formula:67f9d569-11f6-4d60-8005-fa087a937329}} where {{formula:5459e5f6-2c16-45de-a943-05da0fdca1c5}} and {{formula:27cbe081-6d87-4cf2-a11c-2dbdfb8b1... | m | ad3416684a242c021855d12d5bd06d29 |
Support vector machines {{cite:2a06a9c650d9412efa5fd463b4233c8c3703903a}} partition their input space in regions
using hyperplanes that separate the training inputs according to
their labels.
They hyperplanes are chosen (i.e., learned during training) to maximize
their distance (called margin) to their closest training... | m | 528b6ffeb3fc515cc5467ed1ad139d44 |
Hand-designed networks found in the literature {{cite:585273b83cbde6082aeca723f8a6253ed3bf77a9}}, {{cite:f382db3ba761916da2ea1893ac69cd5bd766b090}} are compared to the best weight agnostic networks found for each task. We compare the mean performance over 100 trials under 4 conditions:
| r | c19db17b9a4a54f0ee01c28d41026c98 |
{{cite:080d7c15a02a0b378134849b2e5caa79d4009bbd}} 2021
{{table:8082d1bf-8827-4bc6-85a1-2bff5bf9ba41}} | m | c3208ad4f660f44a3cfcea2edf402078 |
Third, there is a fundamental mathematical question of characterizing the attractor whose existence we postulate in Claim REF . It is likely that symmetric bifurcation theory {{cite:6b4b6f7d10850e661e2b72480928ce11bfeced4b}} will provide a set of tools to enable this analysis.
Answering these questions will push forwar... | d | ab1d2f787bfb320079abea0d3bd61827 |
Recent advancements in Internet of Things (IoT) and 5G wireless networks have paved a way towards realizing new application such as surveillance, augmented/virtual reality, and face recognition, which usually are both computation and caching resource intensive. For battery-powered and resource-constrained devices, such... | i | 871a9575ebac8430e62bbd5fd4b7d2d2 |
Our implementation of the copy generation in the Transformer is inspired by {{cite:534a278402ba29476c1cddc488754b23dd9ad4bc}}. We use the final encoder attention vector and produce a copying vector emphasising each input token relative to its attention weight {{formula:ae0ffe00-1dff-4e67-954a-155e9da274bb}} , Equation ... | m | 14f5d42c7086ac51c55b1d58632a694d |
In the modern era, observations may have a comparable or even larger dimension than the number of samples. So the dimension of parameters cannot be considered as fixed. In order to perform consistent estimation, statisticians need to assume the underlying parameters are sparse(i.e., the parameters contain many zeros), ... | i | c39136899f897084aad720637a473ede |
We may and shall assume that {{formula:8b282bff-4577-4db6-8164-493f889f183b}} otherwise the statement trivially holds.
Let {{formula:e9555893-c12a-4061-b6ba-42762e7e6569}} , that is, {{formula:83e3a7b2-53be-432a-aed0-792d7f449df8}} and {{formula:a692ef1c-316a-4b96-a271-3adb7967462a}} .
It is easy to check that {{form... | r | 520c1e9f4df254cd801ab29b506cb26c |
With regard to the second-order derivatives, we have the following counterpart of Yau's {{formula:6e851a23-a4df-4699-bafc-98d058149288}} estimate {{cite:cc5cf144d996e52b5933a42da0e15e47d9ecda79}}.
| i | dcecccb95482e4bb2afafe2a50225504 |
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