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DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues
| 17 |
iclr
| 5 | 1 |
2023-06-18 09:24:51.189000
|
https://github.com/rishabhjoshi/DialoGraph_ICLR21
| 12 |
Dialograph: Incorporating interpretable strategy-graph networks into negotiation dialogues
|
https://scholar.google.com/scholar?cluster=13588714176146046430&hl=en&as_sdt=0,33
| 3 | 2,021 |
Multi-Time Attention Networks for Irregularly Sampled Time Series
| 67 |
iclr
| 16 | 5 |
2023-06-18 09:24:51.391000
|
https://github.com/reml-lab/mTAN
| 76 |
Multi-time attention networks for irregularly sampled time series
|
https://scholar.google.com/scholar?cluster=6069781928255471893&hl=en&as_sdt=0,33
| 3 | 2,021 |
SEED: Self-supervised Distillation For Visual Representation
| 116 |
iclr
| 11 | 1 |
2023-06-18 09:24:51.595000
|
https://github.com/jacobswan1/SEED
| 32 |
Seed: Self-supervised distillation for visual representation
|
https://scholar.google.com/scholar?cluster=8472207324878329601&hl=en&as_sdt=0,6
| 2 | 2,021 |
Effective and Efficient Vote Attack on Capsule Networks
| 14 |
iclr
| 1 | 0 |
2023-06-18 09:24:51.798000
|
https://github.com/JindongGu/VoteAttack
| 8 |
Effective and efficient vote attack on capsule networks
|
https://scholar.google.com/scholar?cluster=17735896064607887754&hl=en&as_sdt=0,5
| 1 | 2,021 |
Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization
| 44 |
iclr
| 1 | 2 |
2023-06-18 09:24:52.001000
|
https://github.com/kaidic/HAR
| 30 |
Heteroskedastic and imbalanced deep learning with adaptive regularization
|
https://scholar.google.com/scholar?cluster=5140614749291211049&hl=en&as_sdt=0,39
| 1 | 2,021 |
Neural Thompson Sampling
| 60 |
iclr
| 3 | 0 |
2023-06-18 09:24:52.204000
|
https://github.com/ZeroWeight/NeuralTS
| 9 |
Neural thompson sampling
|
https://scholar.google.com/scholar?cluster=5718992412450799651&hl=en&as_sdt=0,31
| 1 | 2,021 |
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics
| 42 |
iclr
| 3 | 1 |
2023-06-18 09:24:52.408000
|
https://github.com/danielkunin/neural-mechanics
| 18 |
Neural mechanics: Symmetry and broken conservation laws in deep learning dynamics
|
https://scholar.google.com/scholar?cluster=8694895381782484369&hl=en&as_sdt=0,11
| 3 | 2,021 |
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction
| 18 |
iclr
| 2 | 0 |
2023-06-18 09:24:52.618000
|
https://github.com/1Konny/HierarchicalVideoPrediction
| 21 |
Revisiting hierarchical approach for persistent long-term video prediction
|
https://scholar.google.com/scholar?cluster=3252280345602395682&hl=en&as_sdt=0,34
| 3 | 2,021 |
Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue System
| 31 |
iclr
| 0 | 2 |
2023-06-18 09:24:52.824000
|
https://github.com/mikezhang95/HDNO
| 18 |
Modelling hierarchical structure between dialogue policy and natural language generator with option framework for task-oriented dialogue system
|
https://scholar.google.com/scholar?cluster=10305196769092538999&hl=en&as_sdt=0,5
| 3 | 2,021 |
Categorical Normalizing Flows via Continuous Transformations
| 20 |
iclr
| 11 | 1 |
2023-06-18 09:24:53.027000
|
https://github.com/phlippe/CategoricalNF
| 51 |
Categorical normalizing flows via continuous transformations
|
https://scholar.google.com/scholar?cluster=3325488278431925119&hl=en&as_sdt=0,18
| 3 | 2,021 |
Learning to Represent Action Values as a Hypergraph on the Action Vertices
| 11 |
iclr
| 6 | 0 |
2023-06-18 09:24:53.230000
|
https://github.com/atavakol/action-hypergraph-networks
| 19 |
Learning to represent action values as a hypergraph on the action vertices
|
https://scholar.google.com/scholar?cluster=8032720011491457722&hl=en&as_sdt=0,5
| 1 | 2,021 |
Lifelong Learning of Compositional Structures
| 25 |
iclr
| 8 | 1 |
2023-06-18 09:24:53.433000
|
https://github.com/GRASP-ML/Mendez2020Compositional
| 12 |
Lifelong learning of compositional structures
|
https://scholar.google.com/scholar?cluster=11061523929398124661&hl=en&as_sdt=0,5
| 5 | 2,021 |
Creative Sketch Generation
| 42 |
iclr
| 13 | 0 |
2023-06-18 09:24:53.643000
|
https://github.com/facebookresearch/DoodlerGAN
| 101 |
Creative sketch generation
|
https://scholar.google.com/scholar?cluster=2511600747232100268&hl=en&as_sdt=0,5
| 8 | 2,021 |
Concept Learners for Few-Shot Learning
| 61 |
iclr
| 13 | 6 |
2023-06-18 09:24:53.863000
|
https://github.com/snap-stanford/comet
| 104 |
Concept learners for few-shot learning
|
https://scholar.google.com/scholar?cluster=14029381289602972954&hl=en&as_sdt=0,5
| 8 | 2,021 |
DeLighT: Deep and Light-weight Transformer
| 88 |
iclr
| 50 | 7 |
2023-06-18 09:24:54.066000
|
https://github.com/sacmehta/delight
| 443 |
Delight: Deep and light-weight transformer
|
https://scholar.google.com/scholar?cluster=13638554196274165568&hl=en&as_sdt=0,47
| 14 | 2,021 |
Mastering Atari with Discrete World Models
| 385 |
iclr
| 183 | 6 |
2023-06-18 09:24:54.269000
|
https://github.com/danijar/dreamerv2
| 767 |
Mastering atari with discrete world models
|
https://scholar.google.com/scholar?cluster=2696098032395844049&hl=en&as_sdt=0,5
| 27 | 2,021 |
Learning Neural Event Functions for Ordinary Differential Equations
| 76 |
iclr
| 848 | 61 |
2023-06-18 09:24:54.472000
|
https://github.com/rtqichen/torchdiffeq
| 4,676 |
Learning neural event functions for ordinary differential equations
|
https://scholar.google.com/scholar?cluster=15727092148990578310&hl=en&as_sdt=0,1
| 123 | 2,021 |
Contemplating Real-World Object Classification
| 6 |
iclr
| 0 | 0 |
2023-06-18 09:24:54.675000
|
https://github.com/aliborji/ObjectNetReanalysis
| 15 |
Contemplating real-world object classification
|
https://scholar.google.com/scholar?cluster=6078463704696071400&hl=en&as_sdt=0,14
| 3 | 2,021 |
Neural Spatio-Temporal Point Processes
| 56 |
iclr
| 16 | 5 |
2023-06-18 09:24:54.878000
|
https://github.com/facebookresearch/neural_stpp
| 85 |
Neural spatio-temporal point processes
|
https://scholar.google.com/scholar?cluster=6976487564397209584&hl=en&as_sdt=0,33
| 10 | 2,021 |
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
| 105 |
iclr
| 5 | 0 |
2023-06-18 09:24:55.081000
|
https://github.com/UCSC-REAL/cores
| 27 |
Learning with instance-dependent label noise: A sample sieve approach
|
https://scholar.google.com/scholar?cluster=1816427362683189606&hl=en&as_sdt=0,22
| 4 | 2,021 |
Unbiased Teacher for Semi-Supervised Object Detection
| 254 |
iclr
| 82 | 32 |
2023-06-18 09:24:55.284000
|
https://github.com/facebookresearch/unbiased-teacher
| 393 |
Unbiased teacher for semi-supervised object detection
|
https://scholar.google.com/scholar?cluster=860392753310305868&hl=en&as_sdt=0,33
| 17 | 2,021 |
Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks
| 183 |
iclr
| 13 | 0 |
2023-06-18 09:24:55.487000
|
https://github.com/bboylyg/NAD
| 98 |
Neural attention distillation: Erasing backdoor triggers from deep neural networks
|
https://scholar.google.com/scholar?cluster=11473045902984731830&hl=en&as_sdt=0,22
| 2 | 2,021 |
Contrastive Learning with Adversarial Perturbations for Conditional Text Generation
| 66 |
iclr
| 3 | 3 |
2023-06-18 09:24:55.690000
|
https://github.com/seanie12/CLAPS
| 77 |
Contrastive learning with adversarial perturbations for conditional text generation
|
https://scholar.google.com/scholar?cluster=13654340302052439773&hl=en&as_sdt=0,5
| 4 | 2,021 |
Text Generation by Learning from Demonstrations
| 34 |
iclr
| 6 | 0 |
2023-06-18 09:24:55.893000
|
https://github.com/yzpang/gold-off-policy-text-gen-iclr21
| 42 |
Text generation by learning from demonstrations
|
https://scholar.google.com/scholar?cluster=7301017997862747001&hl=en&as_sdt=0,5
| 3 | 2,021 |
Learning Long-term Visual Dynamics with Region Proposal Interaction Networks
| 40 |
iclr
| 12 | 0 |
2023-06-18 09:24:56.097000
|
https://github.com/HaozhiQi/RPIN
| 110 |
Learning long-term visual dynamics with region proposal interaction networks
|
https://scholar.google.com/scholar?cluster=12876852900832613209&hl=en&as_sdt=0,5
| 5 | 2,021 |
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations
| 21 |
iclr
| 7 | 5 |
2023-06-18 09:24:56.301000
|
https://github.com/transmuteAI/ChipNet
| 20 |
Chipnet: Budget-aware pruning with heaviside continuous approximations
|
https://scholar.google.com/scholar?cluster=18315278844626956767&hl=en&as_sdt=0,5
| 4 | 2,021 |
Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
| 17 |
iclr
| 0 | 1 |
2023-06-18 09:24:56.504000
|
https://github.com/INK-USC/deceive-KG-models
| 4 |
Learning to deceive knowledge graph augmented models via targeted perturbation
|
https://scholar.google.com/scholar?cluster=10251964553453690301&hl=en&as_sdt=0,5
| 5 | 2,021 |
IEPT: Instance-Level and Episode-Level Pretext Tasks for Few-Shot Learning
| 67 |
iclr
| 4 | 5 |
2023-06-18 09:24:56.708000
|
https://github.com/rucmlcv/IEPT_FSL
| 32 |
IEPT: Instance-level and episode-level pretext tasks for few-shot learning
|
https://scholar.google.com/scholar?cluster=13782822580168472981&hl=en&as_sdt=0,33
| 1 | 2,021 |
Training with Quantization Noise for Extreme Model Compression
| 163 |
iclr
| 5,883 | 1,031 |
2023-06-18 09:24:56.912000
|
https://github.com/pytorch/fairseq
| 26,500 |
Training with quantization noise for extreme model compression
|
https://scholar.google.com/scholar?cluster=10846655234663420432&hl=en&as_sdt=0,38
| 411 | 2,021 |
Distilling Knowledge from Reader to Retriever for Question Answering
| 113 |
iclr
| 98 | 18 |
2023-06-18 09:24:57.115000
|
https://github.com/facebookresearch/FiD
| 410 |
Distilling knowledge from reader to retriever for question answering
|
https://scholar.google.com/scholar?cluster=18188741483036284668&hl=en&as_sdt=0,24
| 8 | 2,021 |
not-MIWAE: Deep Generative Modelling with Missing not at Random Data
| 35 |
iclr
| 2 | 1 |
2023-06-18 09:24:57.318000
|
https://github.com/nbip/notMIWAE
| 10 |
not-MIWAE: Deep generative modelling with missing not at random data
|
https://scholar.google.com/scholar?cluster=6702862707745789629&hl=en&as_sdt=0,5
| 1 | 2,021 |
Learning with AMIGo: Adversarially Motivated Intrinsic Goals
| 107 |
iclr
| 7 | 6 |
2023-06-18 09:24:57.522000
|
https://github.com/facebookresearch/adversarially-motivated-intrinsic-goals
| 60 |
Learning with amigo: Adversarially motivated intrinsic goals
|
https://scholar.google.com/scholar?cluster=10840346887158319600&hl=en&as_sdt=0,5
| 13 | 2,021 |
CaPC Learning: Confidential and Private Collaborative Learning
| 41 |
iclr
| 6 | 0 |
2023-06-18 09:24:57.726000
|
https://github.com/cleverhans-lab/capc-iclr
| 25 |
Capc learning: Confidential and private collaborative learning
|
https://scholar.google.com/scholar?cluster=10267580043538476414&hl=en&as_sdt=0,33
| 2 | 2,021 |
Self-supervised Representation Learning with Relative Predictive Coding
| 25 |
iclr
| 1 | 0 |
2023-06-18 09:24:57.929000
|
https://github.com/martinmamql/relative_predictive_coding
| 17 |
Self-supervised representation learning with relative predictive coding
|
https://scholar.google.com/scholar?cluster=17809486725301186145&hl=en&as_sdt=0,33
| 3 | 2,021 |
On the Impossibility of Global Convergence in Multi-Loss Optimization
| 28 |
iclr
| 0 | 0 |
2023-06-18 09:24:58.134000
|
https://github.com/aletcher/impossibility-global-convergence
| 1 |
On the impossibility of global convergence in multi-loss optimization
|
https://scholar.google.com/scholar?cluster=12737917021502438759&hl=en&as_sdt=0,8
| 2 | 2,021 |
Discrete Graph Structure Learning for Forecasting Multiple Time Series
| 90 |
iclr
| 32 | 10 |
2023-06-18 09:24:58.337000
|
https://github.com/chaoshangcs/GTS
| 138 |
Discrete graph structure learning for forecasting multiple time series
|
https://scholar.google.com/scholar?cluster=10547313552848250901&hl=en&as_sdt=0,5
| 1 | 2,021 |
Contrastive Learning with Hard Negative Samples
| 372 |
iclr
| 29 | 4 |
2023-06-18 09:24:58.541000
|
https://github.com/joshr17/HCL
| 209 |
Contrastive learning with hard negative samples
|
https://scholar.google.com/scholar?cluster=9395538845107330163&hl=en&as_sdt=0,33
| 4 | 2,021 |
Sliced Kernelized Stein Discrepancy
| 32 |
iclr
| 1 | 0 |
2023-06-18 09:24:58.754000
|
https://github.com/WenboGong/Sliced_Kernelized_Stein_Discrepancy
| 1 |
Sliced kernelized Stein discrepancy
|
https://scholar.google.com/scholar?cluster=2996953406646769622&hl=en&as_sdt=0,33
| 1 | 2,021 |
Denoising Diffusion Implicit Models
| 888 |
iclr
| 117 | 9 |
2023-06-18 09:24:58.968000
|
https://github.com/ermongroup/ddim
| 739 |
Denoising diffusion implicit models
|
https://scholar.google.com/scholar?cluster=15692403916484267912&hl=en&as_sdt=0,5
| 7 | 2,021 |
Hierarchical Reinforcement Learning by Discovering Intrinsic Options
| 39 |
iclr
| 5 | 0 |
2023-06-18 09:24:59.171000
|
https://github.com/jesbu1/hidio
| 33 |
Hierarchical reinforcement learning by discovering intrinsic options
|
https://scholar.google.com/scholar?cluster=13774457898597661274&hl=en&as_sdt=0,31
| 3 | 2,021 |
Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval
| 31 |
iclr
| 20 | 10 |
2023-06-18 09:24:59.375000
|
https://github.com/facebookresearch/multihop_dense_retrieval
| 193 |
Answering complex open-domain questions with multi-hop dense retrieval
|
https://scholar.google.com/scholar?cluster=950426100300537362&hl=en&as_sdt=0,11
| 10 | 2,021 |
Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective
| 68 |
iclr
| 8 | 2 |
2023-06-18 09:24:59.579000
|
https://github.com/bellymonster/Weighted-Soft-Label-Distillation
| 51 |
Rethinking soft labels for knowledge distillation: A bias-variance tradeoff perspective
|
https://scholar.google.com/scholar?cluster=3419265116885877699&hl=en&as_sdt=0,33
| 2 | 2,021 |
Learning to Set Waypoints for Audio-Visual Navigation
| 66 |
iclr
| 50 | 35 |
2023-06-18 09:24:59.782000
|
https://github.com/facebookresearch/sound-spaces
| 265 |
Learning to set waypoints for audio-visual navigation
|
https://scholar.google.com/scholar?cluster=3241754597982195177&hl=en&as_sdt=0,34
| 14 | 2,021 |
Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective
| 144 |
iclr
| 31 | 1 |
2023-06-18 09:24:59.985000
|
https://github.com/VITA-Group/TENAS
| 160 |
Neural architecture search on imagenet in four gpu hours: A theoretically inspired perspective
|
https://scholar.google.com/scholar?cluster=8900374722066786979&hl=en&as_sdt=0,33
| 5 | 2,021 |
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning
| 129 |
iclr
| 15 | 3 |
2023-06-18 09:25:00.188000
|
https://github.com/wyjeong/FedMatch
| 58 |
Federated semi-supervised learning with inter-client consistency & disjoint learning
|
https://scholar.google.com/scholar?cluster=7065606493210904394&hl=en&as_sdt=0,44
| 1 | 2,021 |
Representation Learning for Sequence Data with Deep Autoencoding Predictive Components
| 11 |
iclr
| 2 | 0 |
2023-06-18 09:25:00.391000
|
https://github.com/JunwenBai/DAPC
| 9 |
Representation learning for sequence data with deep autoencoding predictive components
|
https://scholar.google.com/scholar?cluster=14928540791785699734&hl=en&as_sdt=0,5
| 2 | 2,021 |
Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search
| 21 |
iclr
| 6 | 0 |
2023-06-18 09:25:00.595000
|
https://github.com/PerdonLiu/CSE-Autoloss
| 56 |
Loss function discovery for object detection via convergence-simulation driven search
|
https://scholar.google.com/scholar?cluster=14213953429648652822&hl=en&as_sdt=0,5
| 2 | 2,021 |
Effective Abstract Reasoning with Dual-Contrast Network
| 15 |
iclr
| 1 | 0 |
2023-06-18 09:25:00.798000
|
https://github.com/visiontao/dcnet
| 9 |
Effective abstract reasoning with dual-contrast network
|
https://scholar.google.com/scholar?cluster=17541928737490000806&hl=en&as_sdt=0,5
| 1 | 2,021 |
Set Prediction without Imposing Structure as Conditional Density Estimation
| 9 |
iclr
| 1 | 0 |
2023-06-18 09:25:01.001000
|
https://github.com/davzha/DESP
| 5 |
Set prediction without imposing structure as conditional density estimation
|
https://scholar.google.com/scholar?cluster=3129155688534171639&hl=en&as_sdt=0,5
| 1 | 2,021 |
Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation
| 49 |
iclr
| 7 | 4 |
2023-06-18 09:25:01.208000
|
https://github.com/TTN-YKK/Clustering_friendly_representation_learning
| 48 |
Clustering-friendly representation learning via instance discrimination and feature decorrelation
|
https://scholar.google.com/scholar?cluster=11187160992598838223&hl=en&as_sdt=0,5
| 2 | 2,021 |
Language-Agnostic Representation Learning of Source Code from Structure and Context
| 95 |
iclr
| 29 | 3 |
2023-06-18 09:25:01.412000
|
https://github.com/danielzuegner/code-transformer
| 147 |
Language-agnostic representation learning of source code from structure and context
|
https://scholar.google.com/scholar?cluster=4574202408084137820&hl=en&as_sdt=0,5
| 9 | 2,021 |
Training GANs with Stronger Augmentations via Contrastive Discriminator
| 48 |
iclr
| 25 | 1 |
2023-06-18 09:25:01.615000
|
https://github.com/jh-jeong/ContraD
| 182 |
Training gans with stronger augmentations via contrastive discriminator
|
https://scholar.google.com/scholar?cluster=14845144713420069894&hl=en&as_sdt=0,5
| 11 | 2,021 |
Continual learning in recurrent neural networks
| 25 |
iclr
| 6 | 0 |
2023-06-18 09:25:01.834000
|
https://github.com/mariacer/cl_in_rnns
| 34 |
Continual learning in recurrent neural networks
|
https://scholar.google.com/scholar?cluster=11490619605153761902&hl=en&as_sdt=0,15
| 6 | 2,021 |
A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention
| 32 |
iclr
| 12 | 4 |
2023-06-18 09:25:02.038000
|
https://github.com/claying/OTK
| 99 |
A trainable optimal transport embedding for feature aggregation and its relationship to attention
|
https://scholar.google.com/scholar?cluster=10719309701133188267&hl=en&as_sdt=0,31
| 3 | 2,021 |
Noise or Signal: The Role of Image Backgrounds in Object Recognition
| 227 |
iclr
| 15 | 2 |
2023-06-18 09:25:02.241000
|
https://github.com/MadryLab/backgrounds_challenge
| 125 |
Noise or signal: The role of image backgrounds in object recognition
|
https://scholar.google.com/scholar?cluster=14729938011425134088&hl=en&as_sdt=0,33
| 8 | 2,021 |
Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation
| 56 |
iclr
| 2 | 7 |
2023-06-18 09:25:02.446000
|
https://github.com/KelestZ/Latent2im
| 43 |
Enjoy your editing: Controllable gans for image editing via latent space navigation
|
https://scholar.google.com/scholar?cluster=15259069119096220128&hl=en&as_sdt=0,47
| 4 | 2,021 |
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
| 141 |
iclr
| 8 | 4 |
2023-06-18 09:25:02.659000
|
https://github.com/cassidylaidlaw/perceptual-advex
| 50 |
Perceptual adversarial robustness: Defense against unseen threat models
|
https://scholar.google.com/scholar?cluster=8526799141352056555&hl=en&as_sdt=0,5
| 2 | 2,021 |
Zero-Cost Proxies for Lightweight NAS
| 148 |
iclr
| 15 | 7 |
2023-06-18 09:25:02.865000
|
https://github.com/mohsaied/zero-cost-nas
| 132 |
Zero-cost proxies for lightweight nas
|
https://scholar.google.com/scholar?cluster=9734890465405015230&hl=en&as_sdt=0,33
| 8 | 2,021 |
Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit
| 12 |
iclr
| 178 | 119 |
2023-06-18 09:25:03.069000
|
https://github.com/google/uncertainty-baselines
| 1,244 |
Exploring the uncertainty properties of neural networks' implicit priors in the infinite-width limit
|
https://scholar.google.com/scholar?cluster=4194918161901179822&hl=en&as_sdt=0,48
| 20 | 2,021 |
DC3: A learning method for optimization with hard constraints
| 75 |
iclr
| 15 | 1 |
2023-06-18 09:25:03.272000
|
https://github.com/locuslab/DC3
| 86 |
DC3: A learning method for optimization with hard constraints
|
https://scholar.google.com/scholar?cluster=2253295560281589124&hl=en&as_sdt=0,5
| 5 | 2,021 |
Shape-Texture Debiased Neural Network Training
| 78 |
iclr
| 9 | 2 |
2023-06-18 09:25:03.477000
|
https://github.com/LiYingwei/ShapeTextureDebiasedTraining
| 104 |
Shape-texture debiased neural network training
|
https://scholar.google.com/scholar?cluster=13815083807768708857&hl=en&as_sdt=0,5
| 6 | 2,021 |
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
| 78 |
iclr
| 4 | 1 |
2023-06-18 09:25:03.680000
|
https://github.com/HazyResearch/model-patching
| 40 |
Model patching: Closing the subgroup performance gap with data augmentation
|
https://scholar.google.com/scholar?cluster=501938357242145399&hl=en&as_sdt=0,44
| 17 | 2,021 |
Linear Mode Connectivity in Multitask and Continual Learning
| 59 |
iclr
| 1 | 0 |
2023-06-18 09:25:03.885000
|
https://github.com/imirzadeh/MC-SGD
| 9 |
Linear mode connectivity in multitask and continual learning
|
https://scholar.google.com/scholar?cluster=10468811797723946398&hl=en&as_sdt=0,48
| 3 | 2,021 |
Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures
| 32 |
iclr
| 8 | 3 |
2023-06-18 09:25:04.089000
|
https://github.com/phermosilla/IEConv_proteins
| 41 |
Intrinsic-extrinsic convolution and pooling for learning on 3d protein structures
|
https://scholar.google.com/scholar?cluster=10539365407241907053&hl=en&as_sdt=0,5
| 3 | 2,021 |
AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights
| 99 |
iclr
| 53 | 0 |
2023-06-18 09:25:04.292000
|
https://github.com/clovaai/AdamP
| 397 |
Adamp: Slowing down the slowdown for momentum optimizers on scale-invariant weights
|
https://scholar.google.com/scholar?cluster=6696661613902754889&hl=en&as_sdt=0,5
| 13 | 2,021 |
MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering
| 32 |
iclr
| 7 | 2 |
2023-06-18 09:25:04.495000
|
https://github.com/TsungWeiTsai/MiCE
| 44 |
Mice: Mixture of contrastive experts for unsupervised image clustering
|
https://scholar.google.com/scholar?cluster=16325984607726397092&hl=en&as_sdt=0,5
| 1 | 2,021 |
Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?
| 9 |
iclr
| 1 | 0 |
2023-06-18 09:25:04.699000
|
https://github.com/ramp-kits/rl_simulator
| 12 |
Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?
|
https://scholar.google.com/scholar?cluster=13333175726397843154&hl=en&as_sdt=0,33
| 10 | 2,021 |
Private Image Reconstruction from System Side Channels Using Generative Models
| 2 |
iclr
| 1 | 0 |
2023-06-18 09:25:04.902000
|
https://github.com/genSCA/genSCA
| 3 |
Private image reconstruction from system side channels using generative models
|
https://scholar.google.com/scholar?cluster=2761181288645087029&hl=en&as_sdt=0,33
| 2 | 2,021 |
IOT: Instance-wise Layer Reordering for Transformer Structures
| 4 |
iclr
| 1 | 0 |
2023-06-18 09:25:05.106000
|
https://github.com/instance-wise-ordered-transformer/IOT
| 19 |
IoT: Instance-wise layer reordering for transformer structures
|
https://scholar.google.com/scholar?cluster=5895076023042170097&hl=en&as_sdt=0,5
| 2 | 2,021 |
Counterfactual Generative Networks
| 88 |
iclr
| 24 | 3 |
2023-06-18 09:25:05.309000
|
https://github.com/autonomousvision/counterfactual_generative_networks
| 94 |
Counterfactual generative networks
|
https://scholar.google.com/scholar?cluster=445809661981357040&hl=en&as_sdt=0,33
| 8 | 2,021 |
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data
| 54 |
iclr
| 11 | 1 |
2023-06-18 09:25:05.512000
|
https://github.com/CAMTL/CA-MTL
| 48 |
Conditionally adaptive multi-task learning: Improving transfer learning in nlp using fewer parameters & less data
|
https://scholar.google.com/scholar?cluster=814007091936446416&hl=en&as_sdt=0,33
| 3 | 2,021 |
Domain-Robust Visual Imitation Learning with Mutual Information Constraints
| 5 |
iclr
| 2 | 0 |
2023-06-18 09:25:05.715000
|
https://github.com/Aladoro/domain-robust-visual-il
| 11 |
Domain-robust visual imitation learning with mutual information constraints
|
https://scholar.google.com/scholar?cluster=18023915525010137640&hl=en&as_sdt=0,5
| 1 | 2,021 |
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
| 82 |
iclr
| 15 | 8 |
2023-06-18 09:25:05.919000
|
https://github.com/sanatonek/TNC_representation_learning
| 86 |
Unsupervised representation learning for time series with temporal neighborhood coding
|
https://scholar.google.com/scholar?cluster=12306257235943010010&hl=en&as_sdt=0,6
| 1 | 2,021 |
Enforcing robust control guarantees within neural network policies
| 58 |
iclr
| 10 | 0 |
2023-06-18 09:25:06.123000
|
https://github.com/locuslab/robust-nn-control
| 48 |
Enforcing robust control guarantees within neural network policies
|
https://scholar.google.com/scholar?cluster=18128961654135874405&hl=en&as_sdt=0,33
| 7 | 2,021 |
Active Contrastive Learning of Audio-Visual Video Representations
| 57 |
iclr
| 5 | 2 |
2023-06-18 09:25:06.327000
|
https://github.com/yunyikristy/CM-ACC
| 18 |
Active contrastive learning of audio-visual video representations
|
https://scholar.google.com/scholar?cluster=1763906632624707840&hl=en&as_sdt=0,26
| 3 | 2,021 |
Efficient Wasserstein Natural Gradients for Reinforcement Learning
| 12 |
iclr
| 3 | 0 |
2023-06-18 09:25:06.533000
|
https://github.com/tedmoskovitz/WNPG
| 9 |
Efficient wasserstein natural gradients for reinforcement learning
|
https://scholar.google.com/scholar?cluster=18097668228161879279&hl=en&as_sdt=0,5
| 1 | 2,021 |
Probing BERT in Hyperbolic Spaces
| 19 |
iclr
| 5 | 0 |
2023-06-18 09:25:06.736000
|
https://github.com/FranxYao/PoincareProbe
| 43 |
Probing BERT in hyperbolic spaces
|
https://scholar.google.com/scholar?cluster=17283548434643857820&hl=en&as_sdt=0,5
| 6 | 2,021 |
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning
| 29 |
iclr
| 23 | 1 |
2023-06-18 09:25:06.944000
|
https://github.com/wangren09/MetaAdv
| 73 |
On fast adversarial robustness adaptation in model-agnostic meta-learning
|
https://scholar.google.com/scholar?cluster=16465003726106659039&hl=en&as_sdt=0,33
| 7 | 2,021 |
Trusted Multi-View Classification
| 83 |
iclr
| 35 | 0 |
2023-06-18 09:25:07.148000
|
https://github.com/hanmenghan/TMC
| 146 |
Trusted multi-view classification
|
https://scholar.google.com/scholar?cluster=10693215882520722160&hl=en&as_sdt=0,43
| 1 | 2,021 |
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning
| 69 |
iclr
| 7 | 0 |
2023-06-18 09:25:07.352000
|
https://github.com/kibok90/imix
| 74 |
i-mix: A domain-agnostic strategy for contrastive representation learning
|
https://scholar.google.com/scholar?cluster=17225673141444543699&hl=en&as_sdt=0,33
| 3 | 2,021 |
Initialization and Regularization of Factorized Neural Layers
| 19 |
iclr
| 5 | 1 |
2023-06-18 09:25:07.556000
|
https://github.com/microsoft/fnl_paper
| 23 |
Initialization and regularization of factorized neural layers
|
https://scholar.google.com/scholar?cluster=15693677234095389612&hl=en&as_sdt=0,40
| 7 | 2,021 |
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning
| 26 |
iclr
| 1 | 0 |
2023-06-18 09:25:07.760000
|
https://github.com/boschresearch/imax-calibration
| 9 |
Multi-class uncertainty calibration via mutual information maximization-based binning
|
https://scholar.google.com/scholar?cluster=10820552692700202554&hl=en&as_sdt=0,49
| 4 | 2,021 |
Neural ODE Processes
| 47 |
iclr
| 7 | 0 |
2023-06-18 09:25:07.964000
|
https://github.com/crisbodnar/ndp
| 56 |
Neural ode processes
|
https://scholar.google.com/scholar?cluster=12135997685697455587&hl=en&as_sdt=0,5
| 6 | 2,021 |
An Unsupervised Deep Learning Approach for Real-World Image Denoising
| 7 |
iclr
| 4 | 1 |
2023-06-18 09:25:08.168000
|
https://github.com/zhengdharia/Unsupervised_denoising
| 26 |
An unsupervised deep learning approach for real-world image denoising
|
https://scholar.google.com/scholar?cluster=10223621556329070926&hl=en&as_sdt=0,33
| 1 | 2,021 |
Learning Parametrised Graph Shift Operators
| 15 |
iclr
| 0 | 0 |
2023-06-18 09:25:08.371000
|
https://github.com/gdasoulas/pgso
| 2 |
Learning parametrised graph shift operators
|
https://scholar.google.com/scholar?cluster=8306422072823409247&hl=en&as_sdt=0,5
| 2 | 2,021 |
Efficient Conformal Prediction via Cascaded Inference with Expanded Admission
| 25 |
iclr
| 4 | 0 |
2023-06-18 09:25:08.575000
|
https://github.com/ajfisch/conformal-cascades
| 17 |
Efficient conformal prediction via cascaded inference with expanded admission
|
https://scholar.google.com/scholar?cluster=1762284772897717346&hl=en&as_sdt=0,36
| 5 | 2,021 |
GANs Can Play Lottery Tickets Too
| 35 |
iclr
| 7 | 0 |
2023-06-18 09:25:08.778000
|
https://github.com/VITA-Group/GAN-LTH
| 24 |
Gans can play lottery tickets too
|
https://scholar.google.com/scholar?cluster=1236790394387307114&hl=en&as_sdt=0,5
| 9 | 2,021 |
Adaptive Universal Generalized PageRank Graph Neural Network
| 297 |
iclr
| 24 | 0 |
2023-06-18 09:25:08.982000
|
https://github.com/jianhao2016/GPRGNN
| 95 |
Adaptive universal generalized pagerank graph neural network
|
https://scholar.google.com/scholar?cluster=17989054169887872189&hl=en&as_sdt=0,33
| 1 | 2,021 |
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control
| 34 |
iclr
| 2 | 2 |
2023-06-18 09:25:09.185000
|
https://github.com/yobibyte/amorpheus
| 36 |
My body is a cage: the role of morphology in graph-based incompatible control
|
https://scholar.google.com/scholar?cluster=5888918560420712353&hl=en&as_sdt=0,5
| 3 | 2,021 |
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning
| 135 |
iclr
| 8 | 3 |
2023-06-18 09:25:09.388000
|
https://github.com/hongyouc/fedbe
| 28 |
Fedbe: Making bayesian model ensemble applicable to federated learning
|
https://scholar.google.com/scholar?cluster=14031237302830163445&hl=en&as_sdt=0,5
| 1 | 2,021 |
MALI: A memory efficient and reverse accurate integrator for Neural ODEs
| 38 |
iclr
| 6 | 1 |
2023-06-18 09:25:09.592000
|
https://github.com/juntang-zhuang/TorchDiffEqPack
| 39 |
Mali: A memory efficient and reverse accurate integrator for neural odes
|
https://scholar.google.com/scholar?cluster=12010857032543034567&hl=en&as_sdt=0,5
| 1 | 2,021 |
Contrastive Syn-to-Real Generalization
| 38 |
iclr
| 4 | 2 |
2023-06-18 09:25:09.796000
|
https://github.com/NVlabs/CSG
| 30 |
Contrastive syn-to-real generalization
|
https://scholar.google.com/scholar?cluster=14950252501736329080&hl=en&as_sdt=0,5
| 6 | 2,021 |
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting
| 35 |
iclr
| 3 | 1 |
2023-06-18 09:25:10
|
https://github.com/SaynaEbrahimi/Remembering-for-the-Right-Reasons
| 30 |
Remembering for the right reasons: Explanations reduce catastrophic forgetting
|
https://scholar.google.com/scholar?cluster=10259250203808159056&hl=en&as_sdt=0,1
| 4 | 2,021 |
High-Capacity Expert Binary Networks
| 46 |
iclr
| 3 | 0 |
2023-06-18 09:25:10.205000
|
https://github.com/1adrianb/expert-binary-networks
| 22 |
High-capacity expert binary networks
|
https://scholar.google.com/scholar?cluster=12665350713453943927&hl=en&as_sdt=0,14
| 2 | 2,021 |
Learning What To Do by Simulating the Past
| 2 |
iclr
| 7 | 0 |
2023-06-18 09:25:10.408000
|
https://github.com/HumanCompatibleAI/deep-rlsp
| 24 |
Learning what to do by simulating the past
|
https://scholar.google.com/scholar?cluster=15331293852960399558&hl=en&as_sdt=0,50
| 8 | 2,021 |
Progressive Skeletonization: Trimming more fat from a network at initialization
| 49 |
iclr
| 1 | 0 |
2023-06-18 09:25:10.612000
|
https://github.com/naver/force
| 12 |
Progressive skeletonization: Trimming more fat from a network at initialization
|
https://scholar.google.com/scholar?cluster=5929326556429040468&hl=en&as_sdt=0,33
| 5 | 2,021 |
Learning Manifold Patch-Based Representations of Man-Made Shapes
| 21 |
iclr
| 6 | 0 |
2023-06-18 09:25:10.829000
|
https://github.com/dmsm/LearningPatches
| 25 |
Learning manifold patch-based representations of man-made shapes
|
https://scholar.google.com/scholar?cluster=9102520552228338739&hl=en&as_sdt=0,5
| 4 | 2,021 |
Aligning AI With Shared Human Values
| 100 |
iclr
| 24 | 2 |
2023-06-18 09:25:11.033000
|
https://github.com/hendrycks/ethics
| 131 |
Aligning ai with shared human values
|
https://scholar.google.com/scholar?cluster=3779881846531532351&hl=en&as_sdt=0,34
| 6 | 2,021 |
Measuring Massive Multitask Language Understanding
| 161 |
iclr
| 40 | 5 |
2023-06-18 09:25:11.240000
|
https://github.com/hendrycks/test
| 335 |
Measuring massive multitask language understanding
|
https://scholar.google.com/scholar?cluster=17727716530891149102&hl=en&as_sdt=0,5
| 12 | 2,021 |
Towards Robust Neural Networks via Close-loop Control
| 13 |
iclr
| 3 | 0 |
2023-06-18 09:25:11.445000
|
https://github.com/zhuotongchen/Towards-Robust-Neural-Networks-via-Close-loop-Control
| 12 |
Towards robust neural networks via close-loop control
|
https://scholar.google.com/scholar?cluster=3798545379660922122&hl=en&as_sdt=0,5
| 1 | 2,021 |
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