title
stringlengths 8
155
| citations_google_scholar
int64 0
28.9k
| conference
stringclasses 5
values | forks
int64 0
46.3k
| issues
int64 0
12.2k
| lastModified
stringlengths 19
26
| repo_url
stringlengths 26
130
| stars
int64 0
75.9k
| title_google_scholar
stringlengths 8
155
| url_google_scholar
stringlengths 75
206
| watchers
int64 0
2.77k
| year
int64 2.02k
2.02k
|
|---|---|---|---|---|---|---|---|---|---|---|---|
Learning Implicitly Recurrent CNNs Through Parameter Sharing
| 57 |
iclr
| 13 | 1 |
2023-06-18 08:58:14.472000
|
https://github.com/lolemacs/soft-sharing
| 65 |
Learning implicitly recurrent CNNs through parameter sharing
|
https://scholar.google.com/scholar?cluster=15123734257747528548&hl=en&as_sdt=0,33
| 4 | 2,019 |
Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs
| 67 |
iclr
| 18 | 2 |
2023-06-18 08:58:14.673000
|
https://github.com/Sachin19/seq2seq-con
| 76 |
Von mises-fisher loss for training sequence to sequence models with continuous outputs
|
https://scholar.google.com/scholar?cluster=1822338940984352644&hl=en&as_sdt=0,5
| 9 | 2,019 |
Rethinking the Value of Network Pruning
| 1,281 |
iclr
| 307 | 23 |
2023-06-18 08:58:14.874000
|
https://github.com/Eric-mingjie/rethinking-network-pruning
| 1,452 |
Rethinking the value of network pruning
|
https://scholar.google.com/scholar?cluster=3601827758437367761&hl=en&as_sdt=0,33
| 35 | 2,019 |
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
| 158 |
iclr
| 13 | 3 |
2023-06-18 08:58:15.075000
|
https://github.com/xuanqing94/BayesianDefense
| 61 |
Adv-bnn: Improved adversarial defense through robust bayesian neural network
|
https://scholar.google.com/scholar?cluster=16111397550296660225&hl=en&as_sdt=0,10
| 5 | 2,019 |
Caveats for information bottleneck in deterministic scenarios
| 62 |
iclr
| 1 | 0 |
2023-06-18 08:58:15.276000
|
https://github.com/artemyk/ibcurve
| 9 |
Caveats for information bottleneck in deterministic scenarios
|
https://scholar.google.com/scholar?cluster=8561375002982335569&hl=en&as_sdt=0,23
| 5 | 2,019 |
Preferences Implicit in the State of the World
| 54 |
iclr
| 7 | 0 |
2023-06-18 08:58:15.477000
|
https://github.com/HumanCompatibleAI/rlsp
| 40 |
Preferences implicit in the state of the world
|
https://scholar.google.com/scholar?cluster=9659325123261489202&hl=en&as_sdt=0,10
| 8 | 2,019 |
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
| 227 |
iclr
| 34 | 5 |
2023-06-18 08:58:15.677000
|
https://github.com/benathi/fastswa-semi-sup
| 180 |
There are many consistent explanations of unlabeled data: Why you should average
|
https://scholar.google.com/scholar?cluster=16133183473908875555&hl=en&as_sdt=0,47
| 11 | 2,019 |
Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation
| 12 |
iclr
| 22 | 1 |
2023-06-18 08:58:15.878000
|
https://github.com/naver/aqm-plus
| 50 |
Large-scale answerer in questioner's mind for visual dialog question generation
|
https://scholar.google.com/scholar?cluster=7353352535802475325&hl=en&as_sdt=0,43
| 8 | 2,019 |
Delta: Deep Learning Transfer using Feature Map with Attention for Convolutional Networks
| 126 |
iclr
| 12 | 2 |
2023-06-18 08:58:16.079000
|
https://github.com/lixingjian/DELTA
| 63 |
Delta: Deep learning transfer using feature map with attention for convolutional networks
|
https://scholar.google.com/scholar?cluster=1065820725505324380&hl=en&as_sdt=0,3
| 1 | 2,019 |
Texttovec: Deep Contextualized Neural autoregressive Topic Models of Language with Distributed Compositional Prior
| 10 |
iclr
| 5 | 3 |
2023-06-18 08:58:16.280000
|
https://github.com/pgcool/textTOvec
| 24 |
Texttovec: Deep contextualized neural autoregressive topic models of language with distributed compositional prior
|
https://scholar.google.com/scholar?cluster=16604775897027080889&hl=en&as_sdt=0,14
| 3 | 2,019 |
Deep Graph Infomax
| 1,328 |
iclr
| 128 | 10 |
2023-06-18 08:58:16.482000
|
https://github.com/PetarV-/DGI
| 533 |
Deep graph infomax.
|
https://scholar.google.com/scholar?cluster=6675561854020696633&hl=en&as_sdt=0,11
| 11 | 2,019 |
Practical lossless compression with latent variables using bits back coding
| 105 |
iclr
| 20 | 2 |
2023-06-18 08:58:16.684000
|
https://github.com/bits-back/bits-back
| 131 |
Practical lossless compression with latent variables using bits back coding
|
https://scholar.google.com/scholar?cluster=1443052248345328520&hl=en&as_sdt=0,22
| 5 | 2,019 |
Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
| 214 |
iclr
| 50 | 10 |
2023-06-18 08:58:16.885000
|
https://github.com/IC3Net/IC3Net
| 185 |
Learning when to communicate at scale in multiagent cooperative and competitive tasks
|
https://scholar.google.com/scholar?cluster=12298395236200633957&hl=en&as_sdt=0,5
| 4 | 2,019 |
GO Gradient for Expectation-Based Objectives
| 22 |
iclr
| 0 | 0 |
2023-06-18 08:58:17.085000
|
https://github.com/YulaiCong/GOgradient
| 4 |
GO gradient for expectation-based objectives
|
https://scholar.google.com/scholar?cluster=13295613950307692271&hl=en&as_sdt=0,23
| 1 | 2,019 |
h-detach: Modifying the LSTM Gradient Towards Better Optimization
| 40 |
iclr
| 3 | 0 |
2023-06-18 08:58:17.286000
|
https://github.com/bhargav104/h-detach
| 11 |
h-detach: Modifying the LSTM gradient towards better optimization
|
https://scholar.google.com/scholar?cluster=762520068872474914&hl=en&as_sdt=0,14
| 3 | 2,019 |
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
| 136 |
iclr
| 33 | 2 |
2023-06-18 08:58:17.488000
|
https://github.com/ratschlab/SOM-VAE
| 179 |
Som-vae: Interpretable discrete representation learning on time series
|
https://scholar.google.com/scholar?cluster=9836294528958312436&hl=en&as_sdt=0,5
| 11 | 2,019 |
Learning Factorized Multimodal Representations
| 273 |
iclr
| 9 | 4 |
2023-06-18 08:58:17.689000
|
https://github.com/pliang279/factorized
| 56 |
Learning factorized multimodal representations
|
https://scholar.google.com/scholar?cluster=2626823666054989533&hl=en&as_sdt=0,5
| 7 | 2,019 |
Human-level Protein Localization with Convolutional Neural Networks
| 21 |
iclr
| 2 | 1 |
2023-06-18 08:58:17.890000
|
https://github.com/ml-jku/gapnet-pl
| 8 |
Human-level protein localization with convolutional neural networks
|
https://scholar.google.com/scholar?cluster=9993156504734443423&hl=en&as_sdt=0,5
| 6 | 2,019 |
Environment Probing Interaction Policies
| 54 |
iclr
| 1 | 1 |
2023-06-18 08:58:18.091000
|
https://github.com/Wenxuan-Zhou/EPI
| 27 |
Environment probing interaction policies
|
https://scholar.google.com/scholar?cluster=2903789960714905866&hl=en&as_sdt=0,47
| 2 | 2,019 |
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
| 278 |
iclr
| 33 | 2 |
2023-06-18 08:58:18.292000
|
https://github.com/jxhe/vae-lagging-encoder
| 183 |
Lagging inference networks and posterior collapse in variational autoencoders
|
https://scholar.google.com/scholar?cluster=5286759698670808442&hl=en&as_sdt=0,5
| 4 | 2,019 |
Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks
| 235 |
iclr
| 26 | 0 |
2023-06-18 08:58:18.492000
|
https://github.com/reinhardh/supplement_deep_decoder
| 81 |
Deep decoder: Concise image representations from untrained non-convolutional networks
|
https://scholar.google.com/scholar?cluster=5031846359818705791&hl=en&as_sdt=0,5
| 6 | 2,019 |
SNAS: stochastic neural architecture search
| 877 |
iclr
| 24 | 3 |
2023-06-18 08:58:18.693000
|
https://github.com/SNAS-Series/SNAS-Series
| 133 |
SNAS: stochastic neural architecture search
|
https://scholar.google.com/scholar?cluster=13328811299154907405&hl=en&as_sdt=0,33
| 5 | 2,019 |
Global-to-local Memory Pointer Networks for Task-Oriented Dialogue
| 151 |
iclr
| 25 | 1 |
2023-06-18 08:58:18.894000
|
https://github.com/jasonwu0731/GLMP
| 159 |
Global-to-local memory pointer networks for task-oriented dialogue
|
https://scholar.google.com/scholar?cluster=8042905846859720405&hl=en&as_sdt=0,5
| 14 | 2,019 |
InstaGAN: Instance-aware Image-to-Image Translation
| 172 |
iclr
| 161 | 11 |
2023-06-18 08:58:19.096000
|
https://github.com/sangwoomo/instagan
| 836 |
Instagan: Instance-aware image-to-image translation
|
https://scholar.google.com/scholar?cluster=14041898124180765737&hl=en&as_sdt=0,5
| 34 | 2,019 |
Learning Multi-Level Hierarchies with Hindsight
| 199 |
iclr
| 59 | 0 |
2023-06-18 08:58:19.297000
|
https://github.com/andrew-j-levy/Hierarchical-Actor-Critc-HAC-
| 239 |
Learning multi-level hierarchies with hindsight
|
https://scholar.google.com/scholar?cluster=11558193958091287134&hl=en&as_sdt=0,33
| 12 | 2,019 |
Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation
| 143 |
iclr
| 19 | 4 |
2023-06-18 09:09:50.832000
|
https://github.com/hugochan/RL-based-Graph2Seq-for-NQG
| 114 |
Reinforcement learning based graph-to-sequence model for natural question generation
|
https://scholar.google.com/scholar?cluster=5519507630710292821&hl=en&as_sdt=0,5
| 7 | 2,020 |
Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
| 475 |
iclr
| 76 | 4 |
2023-06-18 09:09:51.035000
|
https://github.com/yxgeee/MMT
| 450 |
Mutual mean-teaching: Pseudo label refinery for unsupervised domain adaptation on person re-identification
|
https://scholar.google.com/scholar?cluster=5921437976740591026&hl=en&as_sdt=0,47
| 10 | 2,020 |
Automatically Discovering and Learning New Visual Categories with Ranking Statistics
| 112 |
iclr
| 20 | 4 |
2023-06-18 09:09:51.251000
|
https://github.com/k-han/AutoNovel
| 211 |
Automatically discovering and learning new visual categories with ranking statistics
|
https://scholar.google.com/scholar?cluster=6046841849136229502&hl=en&as_sdt=0,5
| 7 | 2,020 |
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning
| 104 |
iclr
| 11 | 1 |
2023-06-18 09:09:51.455000
|
https://github.com/qlan3/Explorer
| 72 |
Maxmin q-learning: Controlling the estimation bias of q-learning
|
https://scholar.google.com/scholar?cluster=7792637153572320374&hl=en&as_sdt=0,5
| 4 | 2,020 |
DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures
| 89 |
iclr
| 3 | 2 |
2023-06-18 09:09:51.657000
|
https://github.com/yanghr/DeepHoyer
| 29 |
Deephoyer: Learning sparser neural network with differentiable scale-invariant sparsity measures
|
https://scholar.google.com/scholar?cluster=9357831330077087953&hl=en&as_sdt=0,33
| 3 | 2,020 |
Evaluating The Search Phase of Neural Architecture Search
| 226 |
iclr
| 8 | 2 |
2023-06-18 09:09:51.860000
|
https://github.com/kcyu2014/eval-nas
| 49 |
Evaluating the search phase of neural architecture search
|
https://scholar.google.com/scholar?cluster=14035367419965317698&hl=en&as_sdt=0,10
| 4 | 2,020 |
LAMOL: LAnguage MOdeling for Lifelong Language Learning
| 122 |
iclr
| 10 | 1 |
2023-06-18 09:09:52.074000
|
https://github.com/jojotenya/LAMOL
| 82 |
Lamol: Language modeling for lifelong language learning
|
https://scholar.google.com/scholar?cluster=16454938344621096337&hl=en&as_sdt=0,5
| 7 | 2,020 |
Automated Relational Meta-learning
| 83 |
iclr
| 5 | 4 |
2023-06-18 09:09:52.280000
|
https://github.com/huaxiuyao/ARML
| 41 |
Automated relational meta-learning
|
https://scholar.google.com/scholar?cluster=12701522525812856519&hl=en&as_sdt=0,33
| 5 | 2,020 |
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition
| 98 |
iclr
| 2 | 0 |
2023-06-18 09:09:52.483000
|
https://github.com/iclr2020-apd/anonymous_iclr2020_apd_code
| 7 |
Scalable and order-robust continual learning with additive parameter decomposition
|
https://scholar.google.com/scholar?cluster=1824460160917131841&hl=en&as_sdt=0,34
| 1 | 2,020 |
A Learning-based Iterative Method for Solving Vehicle Routing Problems
| 169 |
iclr
| 23 | 5 |
2023-06-18 09:09:52.685000
|
https://github.com/rlopt/l2i
| 84 |
A learning-based iterative method for solving vehicle routing problems
|
https://scholar.google.com/scholar?cluster=17783279286650305146&hl=en&as_sdt=0,47
| 11 | 2,020 |
Ranking Policy Gradient
| 12 |
iclr
| 1 | 0 |
2023-06-18 09:09:52.888000
|
https://github.com/illidanlab/rpg
| 22 |
Ranking policy gradient
|
https://scholar.google.com/scholar?cluster=15054324663691805917&hl=en&as_sdt=0,36
| 3 | 2,020 |
On Mutual Information Maximization for Representation Learning
| 390 |
iclr
| 7,332 | 1,026 |
2023-06-18 09:09:53.091000
|
https://github.com/google-research/google-research
| 29,803 |
On mutual information maximization for representation learning
|
https://scholar.google.com/scholar?cluster=13497843317340085742&hl=en&as_sdt=0,24
| 728 | 2,020 |
Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks
| 198 |
iclr
| 48 | 17 |
2023-06-18 09:09:53.295000
|
https://github.com/yhhhli/APoT_Quantization
| 217 |
Additive powers-of-two quantization: An efficient non-uniform discretization for neural networks
|
https://scholar.google.com/scholar?cluster=15761551970233038392&hl=en&as_sdt=0,5
| 5 | 2,020 |
TabFact: A Large-scale Dataset for Table-based Fact Verification
| 228 |
iclr
| 51 | 0 |
2023-06-18 09:09:53.497000
|
https://github.com/wenhuchen/Table-Fact-Checking
| 324 |
Tabfact: A large-scale dataset for table-based fact verification
|
https://scholar.google.com/scholar?cluster=17043210713635846770&hl=en&as_sdt=0,5
| 10 | 2,020 |
Neural Stored-program Memory
| 29 |
iclr
| 3 | 23 |
2023-06-18 09:09:53.700000
|
https://github.com/thaihungle/NSM
| 14 |
Neural stored-program memory
|
https://scholar.google.com/scholar?cluster=15969516798219653164&hl=en&as_sdt=0,11
| 3 | 2,020 |
Multi-agent Reinforcement Learning for Networked System Control
| 71 |
iclr
| 82 | 3 |
2023-06-18 09:09:53.902000
|
https://github.com/cts198859/deeprl_network
| 309 |
Multi-agent reinforcement learning for networked system control
|
https://scholar.google.com/scholar?cluster=8406297615890251928&hl=en&as_sdt=0,33
| 9 | 2,020 |
FSPool: Learning Set Representations with Featurewise Sort Pooling
| 66 |
iclr
| 8 | 1 |
2023-06-18 09:09:54.105000
|
https://github.com/Cyanogenoid/fspool
| 42 |
Fspool: Learning set representations with featurewise sort pooling
|
https://scholar.google.com/scholar?cluster=3929630154366081815&hl=en&as_sdt=0,5
| 4 | 2,020 |
Are Pre-trained Language Models Aware of Phrases? Simple but Strong Baselines for Grammar Induction
| 77 |
iclr
| 5 | 3 |
2023-06-18 09:09:54.308000
|
https://github.com/galsang/trees_from_transformers
| 28 |
Are pre-trained language models aware of phrases? simple but strong baselines for grammar induction
|
https://scholar.google.com/scholar?cluster=12987326770571285349&hl=en&as_sdt=0,6
| 3 | 2,020 |
Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning
| 54 |
iclr
| 3 | 1 |
2023-06-18 09:09:54.512000
|
https://github.com/netpaladinx/DPMPN
| 20 |
Dynamically pruned message passing networks for large-scale knowledge graph reasoning
|
https://scholar.google.com/scholar?cluster=6314488797301074088&hl=en&as_sdt=0,5
| 3 | 2,020 |
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks
| 101 |
iclr
| 10 | 1 |
2023-06-18 09:09:54.714000
|
https://github.com/P2333/Mixup-Inference
| 58 |
Mixup inference: Better exploiting mixup to defend adversarial attacks
|
https://scholar.google.com/scholar?cluster=17489632663330060721&hl=en&as_sdt=0,34
| 3 | 2,020 |
Theory and Evaluation Metrics for Learning Disentangled Representations
| 66 |
iclr
| 2 | 0 |
2023-06-18 09:09:54.917000
|
https://github.com/clarken92/DisentanglementMetrics
| 15 |
Theory and evaluation metrics for learning disentangled representations
|
https://scholar.google.com/scholar?cluster=7456690520633127745&hl=en&as_sdt=0,41
| 2 | 2,020 |
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness
| 133 |
iclr
| 19 | 1 |
2023-06-18 09:09:55.119000
|
https://github.com/P2333/Max-Mahalanobis-Training
| 87 |
Rethinking softmax cross-entropy loss for adversarial robustness
|
https://scholar.google.com/scholar?cluster=12978417581755318851&hl=en&as_sdt=0,5
| 4 | 2,020 |
The Implicit Bias of Depth: How Incremental Learning Drives Generalization
| 38 |
iclr
| 0 | 0 |
2023-06-18 09:09:55.322000
|
https://github.com/dsgissin/Incremental-Learning
| 7 |
The implicit bias of depth: How incremental learning drives generalization
|
https://scholar.google.com/scholar?cluster=13677656727804857978&hl=en&as_sdt=0,5
| 3 | 2,020 |
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget
| 20 |
iclr
| 530 | 16 |
2023-06-18 09:09:55.524000
|
https://github.com/maximecb/gym-minigrid
| 1,810 |
The variational bandwidth bottleneck: Stochastic evaluation on an information budget
|
https://scholar.google.com/scholar?cluster=5182568436909686711&hl=en&as_sdt=0,8
| 39 | 2,020 |
Robust Local Features for Improving the Generalization of Adversarial Training
| 66 |
iclr
| 3 | 1 |
2023-06-18 09:09:55.727000
|
https://github.com/JHL-HUST/RLFAT
| 13 |
Robust local features for improving the generalization of adversarial training
|
https://scholar.google.com/scholar?cluster=11695646506050122270&hl=en&as_sdt=0,5
| 3 | 2,020 |
Analysis of Video Feature Learning in Two-Stream CNNs on the Example of Zebrafish Swim Bout Classification
| 5 |
iclr
| 2 | 0 |
2023-06-18 09:09:55.930000
|
https://github.com/Benji4/zebrafish-learning
| 7 |
Analysis of video feature learning in two-stream CNNs on the example of zebrafish swim bout classification
|
https://scholar.google.com/scholar?cluster=7291111967926344032&hl=en&as_sdt=0,14
| 1 | 2,020 |
Logic and the 2-Simplicial Transformer
| 2 |
iclr
| 4 | 0 |
2023-06-18 09:09:56.134000
|
https://github.com/dmurfet/2simplicialtransformer
| 15 |
Logic and the -Simplicial Transformer
|
https://scholar.google.com/scholar?cluster=3081517893804157897&hl=en&as_sdt=0,33
| 2 | 2,020 |
Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking
| 59 |
iclr
| 9 | 2 |
2023-06-18 09:09:56.337000
|
https://github.com/anonymousjack/hijacking
| 42 |
Fooling detection alone is not enough: Adversarial attack against multiple object tracking
|
https://scholar.google.com/scholar?cluster=15515055522275518315&hl=en&as_sdt=0,47
| 2 | 2,020 |
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
| 599 |
iclr
| 76 | 8 |
2023-06-18 09:09:56.540000
|
https://github.com/LiJunnan1992/DivideMix
| 456 |
Dividemix: Learning with noisy labels as semi-supervised learning
|
https://scholar.google.com/scholar?cluster=11967955085227307195&hl=en&as_sdt=0,33
| 10 | 2,020 |
Accelerating SGD with momentum for over-parameterized learning
| 62 |
iclr
| 1 | 0 |
2023-06-18 09:09:56.744000
|
https://github.com/ts66395/MaSS
| 5 |
Accelerating sgd with momentum for over-parameterized learning
|
https://scholar.google.com/scholar?cluster=15634725943352892277&hl=en&as_sdt=0,36
| 1 | 2,020 |
A critical analysis of self-supervision, or what we can learn from a single image
| 129 |
iclr
| 8 | 3 |
2023-06-18 09:09:56.947000
|
https://github.com/yukimasano/linear-probes
| 36 |
A critical analysis of self-supervision, or what we can learn from a single image
|
https://scholar.google.com/scholar?cluster=1196793253523325509&hl=en&as_sdt=0,31
| 2 | 2,020 |
Progressive Memory Banks for Incremental Domain Adaptation
| 23 |
iclr
| 2 | 0 |
2023-06-18 09:09:57.151000
|
https://github.com/nabihach/IDA
| 13 |
Progressive memory banks for incremental domain adaptation
|
https://scholar.google.com/scholar?cluster=16171132848868692146&hl=en&as_sdt=0,33
| 2 | 2,020 |
Exploring Model-based Planning with Policy Networks
| 124 |
iclr
| 12 | 4 |
2023-06-18 09:09:57.356000
|
https://github.com/WilsonWangTHU/POPLIN
| 93 |
Exploring model-based planning with policy networks
|
https://scholar.google.com/scholar?cluster=5788425518026701179&hl=en&as_sdt=0,34
| 4 | 2,020 |
Few-shot Text Classification with Distributional Signatures
| 141 |
iclr
| 57 | 0 |
2023-06-18 09:09:57.559000
|
https://github.com/YujiaBao/Distributional-Signatures
| 248 |
Few-shot text classification with distributional signatures
|
https://scholar.google.com/scholar?cluster=4872590605106254296&hl=en&as_sdt=0,14
| 6 | 2,020 |
Adversarial Policies: Attacking Deep Reinforcement Learning
| 299 |
iclr
| 41 | 7 |
2023-06-18 09:09:57.762000
|
https://github.com/HumanCompatibleAI/adversarial-policies
| 241 |
Adversarial policies: Attacking deep reinforcement learning
|
https://scholar.google.com/scholar?cluster=1203868559900085227&hl=en&as_sdt=0,11
| 15 | 2,020 |
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation
| 81 |
iclr
| 3,290 | 589 |
2023-06-18 09:09:57.965000
|
https://github.com/tensorflow/tensor2tensor
| 13,768 |
Videoflow: A conditional flow-based model for stochastic video generation
|
https://scholar.google.com/scholar?cluster=13005087974871140727&hl=en&as_sdt=0,14
| 461 | 2,020 |
GLAD: Learning Sparse Graph Recovery
| 23 |
iclr
| 5 | 0 |
2023-06-18 09:09:58.168000
|
https://github.com/Harshs27/GLAD
| 13 |
GLAD: Learning sparse graph recovery
|
https://scholar.google.com/scholar?cluster=17323993038772593390&hl=en&as_sdt=0,47
| 2 | 2,020 |
FasterSeg: Searching for Faster Real-time Semantic Segmentation
| 150 |
iclr
| 110 | 11 |
2023-06-18 09:09:58.370000
|
https://github.com/TAMU-VITA/FasterSeg
| 515 |
Fasterseg: Searching for faster real-time semantic segmentation
|
https://scholar.google.com/scholar?cluster=11587095836376020772&hl=en&as_sdt=0,5
| 27 | 2,020 |
Semantically-Guided Representation Learning for Self-Supervised Monocular Depth
| 161 |
iclr
| 242 | 79 |
2023-06-18 09:09:58.573000
|
https://github.com/TRI-ML/packnet-sfm
| 1,140 |
Semantically-guided representation learning for self-supervised monocular depth
|
https://scholar.google.com/scholar?cluster=17082069917027724929&hl=en&as_sdt=0,5
| 56 | 2,020 |
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius
| 123 |
iclr
| 7 | 3 |
2023-06-18 09:09:58.776000
|
https://github.com/RuntianZ/macer
| 27 |
Macer: Attack-free and scalable robust training via maximizing certified radius
|
https://scholar.google.com/scholar?cluster=17692253363082747545&hl=en&as_sdt=0,5
| 4 | 2,020 |
GAT: Generative Adversarial Training for Adversarial Example Detection and Robust Classification
| 40 |
iclr
| 0 | 0 |
2023-06-18 09:09:58.979000
|
https://github.com/xuwangyin/GAT-Generative-Adversarial-Training
| 3 |
Gat: Generative adversarial training for adversarial example detection and robust classification
|
https://scholar.google.com/scholar?cluster=11402188250493503654&hl=en&as_sdt=0,5
| 2 | 2,020 |
Variational Recurrent Models for Solving Partially Observable Control Tasks
| 45 |
iclr
| 13 | 0 |
2023-06-18 09:09:59.181000
|
https://github.com/oist-cnru/Variational-Recurrent-Models
| 41 |
Variational recurrent models for solving partially observable control tasks
|
https://scholar.google.com/scholar?cluster=10619641407453895242&hl=en&as_sdt=0,5
| 6 | 2,020 |
Population-Guided Parallel Policy Search for Reinforcement Learning
| 36 |
iclr
| 6 | 1 |
2023-06-18 09:09:59.384000
|
https://github.com/wyjung0625/p3s
| 19 |
Population-guided parallel policy search for reinforcement learning
|
https://scholar.google.com/scholar?cluster=13101828686651859537&hl=en&as_sdt=0,44
| 1 | 2,020 |
Compositional languages emerge in a neural iterated learning model
| 55 |
iclr
| 2 | 4 |
2023-06-18 09:09:59.586000
|
https://github.com/Joshua-Ren/Neural_Iterated_Learning
| 11 |
Compositional languages emerge in a neural iterated learning model
|
https://scholar.google.com/scholar?cluster=12260597755376568294&hl=en&as_sdt=0,5
| 3 | 2,020 |
Black-Box Adversarial Attack with Transferable Model-based Embedding
| 85 |
iclr
| 16 | 2 |
2023-06-18 09:09:59.788000
|
https://github.com/TransEmbedBA/TREMBA
| 52 |
Black-box adversarial attack with transferable model-based embedding
|
https://scholar.google.com/scholar?cluster=2817331092772484407&hl=en&as_sdt=0,5
| 4 | 2,020 |
I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively
| 18 |
iclr
| 3 | 0 |
2023-06-18 09:09:59.991000
|
https://github.com/TAMU-VITA/MAD
| 19 |
I am going MAD: Maximum discrepancy competition for comparing classifiers adaptively
|
https://scholar.google.com/scholar?cluster=7857243656260190793&hl=en&as_sdt=0,5
| 12 | 2,020 |
Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models
| 122 |
iclr
| 6 | 0 |
2023-06-18 09:10:00.194000
|
https://github.com/bloodwass/mixout
| 70 |
Mixout: Effective regularization to finetune large-scale pretrained language models
|
https://scholar.google.com/scholar?cluster=476449558403052711&hl=en&as_sdt=0,33
| 3 | 2,020 |
Deep Network Classification by Scattering and Homotopy Dictionary Learning
| 37 |
iclr
| 7 | 1 |
2023-06-18 09:10:00.397000
|
https://github.com/j-zarka/SparseScatNet
| 22 |
Deep network classification by scattering and homotopy dictionary learning
|
https://scholar.google.com/scholar?cluster=8953532076769179699&hl=en&as_sdt=0,5
| 2 | 2,020 |
Action Semantics Network: Considering the Effects of Actions in Multiagent Systems
| 27 |
iclr
| 7 | 8 |
2023-06-18 09:10:00.599000
|
https://github.com/MAS-anony/ASN
| 26 |
Action semantics network: Considering the effects of actions in multiagent systems
|
https://scholar.google.com/scholar?cluster=12922359203743384074&hl=en&as_sdt=0,47
| 2 | 2,020 |
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing
| 66 |
iclr
| 2 | 0 |
2023-06-18 09:10:00.802000
|
https://github.com/jjy1994/Certify_Topk
| 9 |
Certified robustness for top-k predictions against adversarial perturbations via randomized smoothing
|
https://scholar.google.com/scholar?cluster=12562520033309681005&hl=en&as_sdt=0,1
| 2 | 2,020 |
Optimistic Exploration even with a Pessimistic Initialisation
| 39 |
iclr
| 2 | 0 |
2023-06-18 09:10:01.008000
|
https://github.com/oxwhirl/opiq
| 13 |
Optimistic exploration even with a pessimistic initialisation
|
https://scholar.google.com/scholar?cluster=3638632110441158229&hl=en&as_sdt=0,10
| 4 | 2,020 |
VL-BERT: Pre-training of Generic Visual-Linguistic Representations
| 1,249 |
iclr
| 108 | 20 |
2023-06-18 09:10:01.210000
|
https://github.com/jackroos/VL-BERT
| 715 |
Vl-bert: Pre-training of generic visual-linguistic representations
|
https://scholar.google.com/scholar?cluster=7768062511032572067&hl=en&as_sdt=0,43
| 14 | 2,020 |
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality
| 16 |
iclr
| 3 | 2 |
2023-06-18 09:10:01.413000
|
https://github.com/spitis/deepnorms
| 10 |
An inductive bias for distances: Neural nets that respect the triangle inequality
|
https://scholar.google.com/scholar?cluster=17260770554780214553&hl=en&as_sdt=0,23
| 5 | 2,020 |
NAS evaluation is frustratingly hard
| 164 |
iclr
| 23 | 1 |
2023-06-18 09:10:01.617000
|
https://github.com/antoyang/NAS-Benchmark
| 146 |
NAS evaluation is frustratingly hard
|
https://scholar.google.com/scholar?cluster=12471694483970544806&hl=en&as_sdt=0,5
| 4 | 2,020 |
Order Learning and Its Application to Age Estimation
| 19 |
iclr
| 6 | 9 |
2023-06-18 09:10:01.820000
|
https://github.com/changsukim-ku/order-learning
| 18 |
Order learning and its application to age estimation
|
https://scholar.google.com/scholar?cluster=11437601791215885877&hl=en&as_sdt=0,5
| 2 | 2,020 |
ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning
| 102 |
iclr
| 12 | 1 |
2023-06-18 09:10:02.022000
|
https://github.com/yuweihao/reclor
| 70 |
Reclor: A reading comprehension dataset requiring logical reasoning
|
https://scholar.google.com/scholar?cluster=4598160843843301931&hl=en&as_sdt=0,22
| 2 | 2,020 |
From Variational to Deterministic Autoencoders
| 238 |
iclr
| 14 | 13 |
2023-06-18 09:10:02.225000
|
https://github.com/ParthaEth/Regularized_autoencoders-RAE-
| 112 |
From variational to deterministic autoencoders
|
https://scholar.google.com/scholar?cluster=10583740506297544895&hl=en&as_sdt=0,33
| 4 | 2,020 |
A Fair Comparison of Graph Neural Networks for Graph Classification
| 336 |
iclr
| 48 | 6 |
2023-06-18 09:10:02.428000
|
https://github.com/diningphil/gnn-comparison
| 323 |
A fair comparison of graph neural networks for graph classification
|
https://scholar.google.com/scholar?cluster=3840429300245249800&hl=en&as_sdt=0,46
| 9 | 2,020 |
SAdam: A Variant of Adam for Strongly Convex Functions
| 37 |
iclr
| 1 | 0 |
2023-06-18 09:10:02.632000
|
https://github.com/SAdam-ICLR2020/codes
| 1 |
Sadam: A variant of adam for strongly convex functions
|
https://scholar.google.com/scholar?cluster=4099818587284366739&hl=en&as_sdt=0,47
| 1 | 2,020 |
Few-Shot Learning on graphs via super-Classes based on Graph spectral Measures
| 51 |
iclr
| 6 | 5 |
2023-06-18 09:10:02.835000
|
https://github.com/chauhanjatin10/GraphsFewShot
| 27 |
Few-shot learning on graphs via super-classes based on graph spectral measures
|
https://scholar.google.com/scholar?cluster=14327533105664935166&hl=en&as_sdt=0,38
| 2 | 2,020 |
A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning
| 43 |
iclr
| 0 | 1 |
2023-06-18 09:10:03.038000
|
https://github.com/shrezaei/Target-Agnostic-Attack
| 8 |
A target-agnostic attack on deep models: Exploiting security vulnerabilities of transfer learning
|
https://scholar.google.com/scholar?cluster=15887045580387501339&hl=en&as_sdt=0,5
| 1 | 2,020 |
Option Discovery using Deep Skill Chaining
| 71 |
iclr
| 9 | 2 |
2023-06-18 09:10:03.240000
|
https://github.com/deep-skill-chaining/deep-skill-chaining
| 26 |
Option discovery using deep skill chaining
|
https://scholar.google.com/scholar?cluster=3599079453056617566&hl=en&as_sdt=0,5
| 2 | 2,020 |
Quantifying the Cost of Reliable Photo Authentication via High-Performance Learned Lossy Representations
| 1 |
iclr
| 30 | 4 |
2023-06-18 09:10:03.443000
|
https://github.com/pkorus/neural-imaging
| 139 |
Quantifying the cost of reliable photo authentication via high-performance learned lossy representations
|
https://scholar.google.com/scholar?cluster=1043795359610865764&hl=en&as_sdt=0,5
| 11 | 2,020 |
On the Variance of the Adaptive Learning Rate and Beyond
| 1,557 |
iclr
| 340 | 12 |
2023-06-18 09:10:03.646000
|
https://github.com/LiyuanLucasLiu/RAdam
| 2,494 |
On the variance of the adaptive learning rate and beyond
|
https://scholar.google.com/scholar?cluster=2176563085556003509&hl=en&as_sdt=0,14
| 58 | 2,020 |
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection
| 48 |
iclr
| 11 | 7 |
2023-06-18 09:10:03.849000
|
https://github.com/mtsang/interaction_interpretability
| 34 |
Feature interaction interpretability: A case for explaining ad-recommendation systems via neural interaction detection
|
https://scholar.google.com/scholar?cluster=3857662297580644261&hl=en&as_sdt=0,48
| 5 | 2,020 |
Understanding the Limitations of Variational Mutual Information Estimators
| 138 |
iclr
| 7 | 0 |
2023-06-18 09:10:04.054000
|
https://github.com/ermongroup/smile-mi-estimator
| 58 |
Understanding the limitations of variational mutual information estimators
|
https://scholar.google.com/scholar?cluster=4523141934967854838&hl=en&as_sdt=0,25
| 5 | 2,020 |
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
| 210 |
iclr
| 18 | 2 |
2023-06-18 09:10:04.273000
|
https://github.com/applied-ai-lab/genesis
| 87 |
Genesis: Generative scene inference and sampling with object-centric latent representations
|
https://scholar.google.com/scholar?cluster=12595023313997791876&hl=en&as_sdt=0,5
| 4 | 2,020 |
Language GANs Falling Short
| 185 |
iclr
| 11 | 0 |
2023-06-18 09:10:04.475000
|
https://github.com/pclucas14/GansFallingShort
| 57 |
Language gans falling short
|
https://scholar.google.com/scholar?cluster=5625942263097164405&hl=en&as_sdt=0,5
| 6 | 2,020 |
Reinforced active learning for image segmentation
| 72 |
iclr
| 19 | 1 |
2023-06-18 09:10:04.678000
|
https://github.com/ArantxaCasanova/ralis
| 83 |
Reinforced active learning for image segmentation
|
https://scholar.google.com/scholar?cluster=1054013285080220526&hl=en&as_sdt=0,5
| 4 | 2,020 |
Sign Bits Are All You Need for Black-Box Attacks
| 42 |
iclr
| 4 | 0 |
2023-06-18 09:10:04.882000
|
https://github.com/ash-aldujaili/blackbox-adv-examples-signhunter
| 19 |
Sign bits are all you need for black-box attacks
|
https://scholar.google.com/scholar?cluster=7597354738321523797&hl=en&as_sdt=0,5
| 4 | 2,020 |
Deep Semi-Supervised Anomaly Detection
| 407 |
iclr
| 88 | 17 |
2023-06-18 09:10:05.084000
|
https://github.com/lukasruff/Deep-SAD-PyTorch
| 303 |
Deep semi-supervised anomaly detection
|
https://scholar.google.com/scholar?cluster=5100822312770479848&hl=en&as_sdt=0,5
| 9 | 2,020 |
Minimizing FLOPs to Learn Efficient Sparse Representations
| 30 |
iclr
| 2 | 0 |
2023-06-18 09:10:05.288000
|
https://github.com/biswajitsc/sparse-embed
| 19 |
Minimizing flops to learn efficient sparse representations
|
https://scholar.google.com/scholar?cluster=16391107852895136725&hl=en&as_sdt=0,31
| 4 | 2,020 |
Imitation Learning via Off-Policy Distribution Matching
| 111 |
iclr
| 7,332 | 1,026 |
2023-06-18 09:10:05.491000
|
https://github.com/google-research/google-research
| 29,803 |
Imitation learning via off-policy distribution matching
|
https://scholar.google.com/scholar?cluster=17232131883135762020&hl=en&as_sdt=0,32
| 728 | 2,020 |
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space
| 104 |
iclr
| 33 | 0 |
2023-06-18 09:10:05.693000
|
https://github.com/aspuru-guzik-group/GA
| 80 |
Augmenting genetic algorithms with deep neural networks for exploring the chemical space
|
https://scholar.google.com/scholar?cluster=4690781735136459726&hl=en&as_sdt=0,5
| 6 | 2,020 |
Neural Text Generation With Unlikelihood Training
| 334 |
iclr
| 43 | 7 |
2023-06-18 09:10:05.897000
|
https://github.com/facebookresearch/unlikelihood_training
| 293 |
Neural text generation with unlikelihood training
|
https://scholar.google.com/scholar?cluster=16638535268657480159&hl=en&as_sdt=0,5
| 16 | 2,020 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.