ICLR 2023

1,573 papers

3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction

Jiaqi Guan, Wesley Wei Qian, Xingang Peng, Yufeng Su, Jian Peng

Explicitly Minimizing the Blur Error of Variational Autoencoders

Gustav Bredell, Kyriakos Flouris, Krishna Chaitanya, Ertunc Erdil, Ender Konukoglu

DAG Learning on the Permutahedron

Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt Kusner, Vlad Niculae

Semi-Parametric Inducing Point Networks and Neural Processes

Richa Rastogi, Yair Schiff, Alon Hacohen, Zhaozhi Li, Ian Lee

Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing

Renyu Zhang, Aly A Khan, Robert L. Grossman, Yuxin Chen

Relative Behavioral Attributes: Filling the Gap between Symbolic Goal Specification and Reward Learning from Human Preferences

Lin Guan, Karthik Valmeekam, Subbarao Kambhampati

Federated Learning from Small Datasets

Michael Kamp, Jonas Fischer, Jilles Vreeken

Spatio-temporal point processes with deep non-stationary kernels

Zheng Dong, Xiuyuan Cheng, Yao Xie

Contrastive Corpus Attribution for Explaining Representations

Chris Lin, Hugh Chen, Chanwoo Kim, Su-in Lee

Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions

Raghav Singhal, Mark Goldstein, Rajesh Ranganath

Grounding Graph Network Simulators using Physical Sensor Observations

Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann

DensePure: Understanding Diffusion Models for Adversarial Robustness

Chaowei Xiao, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie

Discovering Evolution Strategies via Meta-Black-Box Optimization

Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard

Towards convergence to Nash equilibria in two-team zero-sum games

Fivos Kalogiannis, Ioannis Panageas, Emmanouil-Vasileios Vlatakis-Gkaragkounis

Personalized Reward Learning with Interaction-Grounded Learning (IGL)

Jessica Maghakian, Paul Mineiro, Kishan Panaganti, Mark Rucker, Akanksha Saran

Make-A-Video: Text-to-Video Generation without Text-Video Data

Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An

Solving Continuous Control via Q-learning

Tim Seyde, Peter Werner, Wilko Schwarting, Igor Gilitschenski, Martin Riedmiller

Hyper-Decision Transformer for Efficient Online Policy Adaptation

Mengdi Xu, Yuchen Lu, Yikang Shen, Shun Zhang, Ding Zhao

Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD

Konstantinos Nikolakakis, Farzin Haddadpour, Amin Karbasi, Dionysios Kalogerias

Bispectral Neural Networks

Sophia Sanborn, Christian A Shewmake, Bruno Olshausen, Christopher J. Hillar

$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games

Yuepeng Yang, Cong Ma

Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning

Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang

Integrating Symmetry into Differentiable Planning with Steerable Convolutions

Linfeng Zhao, Xupeng Zhu, Lingzhi Kong, Robin Walters, Lawson L.S. Wong

DySR: Adaptive Super-Resolution via Algorithm and System Co-design

Syed Zawad, Cheng Li, Zhewei Yao, Elton Zheng, Yuxiong He

Fake It Until You Make It : Towards Accurate Near-Distribution Novelty Detection

Hossein Mirzaei, Mohammadreza Salehi, Sajjad Shahabi, Efstratios Gavves, Cees G. M. Snoek

Analogy-Forming Transformers for Few-Shot 3D Parsing

Nikolaos Gkanatsios, Mayank Singh, Zhaoyuan Fang, Shubham Tulsiani, Katerina Fragkiadaki

Function-space regularized Rényi divergences

Jeremiah Birrell, Yannis Pantazis, Paul Dupuis, Luc Rey-Bellet, Markos Katsoulakis

Why (and When) does Local SGD Generalize Better than SGD?

Xinran Gu, Kaifeng Lyu, Longbo Huang, Sanjeev Arora

Images as Weight Matrices: Sequential Image Generation Through Synaptic Learning Rules

Kazuki Irie, Jürgen Schmidhuber

Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets

Edo Cohen-Karlik, Itamar Menuhin-Gruman, Raja Giryes, Nadav Cohen, Amir Globerson

Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation

Kai Xu, Georgi Ganev, Emile Joubert, Rees Davison, Olivier Van Acker

Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function

Ruijie Zheng, Xiyao Wang, Huazhe Xu, Furong Huang

Adversarial Imitation Learning with Preferences

Aleksandar Taranovic, Andras Gabor Kupcsik, Niklas Freymuth, Gerhard Neumann

Decision Transformer under Random Frame Dropping

Kaizhe Hu, Ray Chen Zheng, Yang Gao, Huazhe Xu

Score-based Continuous-time Discrete Diffusion Models

Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai

Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation

Linfeng Zhao, Huazhe Xu, Lawson L.S. Wong

Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization

Jihwan Jeong, Xiaoyu Wang, Michael Gimelfarb, Hyunwoo Kim, Baher abdulhai

Subsampling in Large Graphs Using Ricci Curvature

Shushan Wu, Huimin Cheng, Jiazhang Cai, Ping Ma, Wenxuan Zhong

A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy

Kaan Ozkara, Antonious M. Girgis, Deepesh Data, Suhas Diggavi

Calibrating the Rigged Lottery: Making All Tickets Reliable

Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani Mallick

Reward Design with Language Models

Minae Kwon, Sang Michael Xie, Kalesha Bullard, Dorsa Sadigh

KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals

Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran

Recitation-Augmented Language Models

Zhiqing Sun, Xuezhi Wang, Yi Tay, Yiming Yang, Denny Zhou

Language models are multilingual chain-of-thought reasoners

Freda Shi, Mirac Suzgun, Markus Freitag, Xuezhi Wang, Suraj Srivats

FIGARO: Controllable Music Generation using Learned and Expert Features

Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hofmann

Using Both Demonstrations and Language Instructions to Efficiently Learn Robotic Tasks

Albert Yu, Ray Mooney

HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers

Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin

On The Specialization of Neural Modules

Devon Jarvis, Richard Klein, Benjamin Rosman, Andrew M Saxe

A VAE for Transformers with Nonparametric Variational Information Bottleneck

James Henderson, Fabio James Fehr

Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation

Jun-Kun Wang, Andre Wibisono

On Achieving Optimal Adversarial Test Error

Justin D. Li, Matus Telgarsky

ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret

Stephen Marcus McAleer, Gabriele Farina, Marc Lanctot, Tuomas Sandholm

Can Neural Networks Learn Implicit Logic from Physical Reasoning?

Aaron Traylor, Roman Feiman, Ellie Pavlick

Transformer-based World Models Are Happy With 100k Interactions

Jan Robine, Marc Höftmann, Tobias Uelwer, Stefan Harmeling

Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments

KAIXIN WANG, Kuangqi Zhou, Bingyi Kang, Jiashi Feng, Shuicheng Yan

LogicDP: Creating Labels for Graph Data via Inductive Logic Programming

Yuan Yang, Faramarz Fekri, James Clayton Kerce, Ali Payani

AGRO: Adversarial discovery of error-prone Groups for Robust Optimization

Bhargavi Paranjape, Pradeep Dasigi, Vivek Srikumar, Luke Zettlemoyer, Hannaneh Hajishirzi

TypeT5: Seq2seq Type Inference using Static Analysis

Jiayi Wei, Greg Durrett, Isil Dillig

Label Propagation with Weak Supervision

Rattana Pukdee, Dylan Sam, Pradeep Kumar Ravikumar, Nina Balcan

FunkNN: Neural Interpolation for Functional Generation

AmirEhsan Khorashadizadeh, Anadi Chaman, Valentin Debarnot, Ivan Dokmanić

Brain-like representational straightening of natural movies in robust feedforward neural networks

Tahereh Toosi, Elias Issa

Promptagator: Few-shot Dense Retrieval From 8 Examples

Zhuyun Dai, Vincent Y Zhao, Ji Ma, Yi Luan, Jianmo Ni

Learning Structured Representations by Embedding Class Hierarchy

Siqi Zeng, Remi Tachet des Combes, Han Zhao

Is Forgetting Less a Good Inductive Bias for Forward Transfer?

Jiefeng Chen, Timothy Nguyen, Dilan Gorur, Arslan Chaudhry

Exploring perceptual straightness in learned visual representations

Anne Harrington, Vasha DuTell, Ayush Tewari, Mark Hamilton, Simon Stent

Efficient approximation of neural population structure and correlations with probabilistic circuits

Koosha Khalvati, Samantha Johnson, Stefan Mihalas, Michael A Buice

Neural Compositional Rule Learning for Knowledge Graph Reasoning

Kewei Cheng, Nesreen Ahmed, Yizhou Sun

Progressive Mix-Up for Few-Shot Supervised Multi-Source Domain Transfer

Ronghang Zhu, Xiang Yu, Sheng Li

A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search

Brandon Trabucco, Gunnar A Sigurdsson, Robinson Piramuthu, Gaurav S. Sukhatme, Ruslan Salakhutdinov

The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes

Alexander Atanasov, Blake Bordelon, Sabarish Sainathan, Cengiz Pehlevan

A Theoretical Framework for Inference and Learning in Predictive Coding Networks

Beren Millidge, Yuhang Song, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz

Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning

Beren Millidge, Yuhang Song, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz

f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation

Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Angel Bautista, Joshua M. Susskind

A Mixture-of-Expert Approach to RL-based Dialogue Management

Yinlam Chow, Azamat Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu

Multiple sequence alignment as a sequence-to-sequence learning problem

Edo Dotan, Yonatan Belinkov, Oren Avram, Elya Wygoda, Noa Ecker

Systematic Rectification of Language Models via Dead-end Analysis

Meng Cao, Mehdi Fatemi, Jackie CK Cheung, Samira Shabanian

Compositionality with Variation Reliably Emerges in Neural Networks

Henry Conklin, Kenny Smith

First Steps Toward Understanding the Extrapolation of Nonlinear Models to Unseen Domains

Kefan Dong, Tengyu Ma

Projective Proximal Gradient Descent for Nonconvex Nonsmooth Optimization: Fast Convergence Without Kurdyka-Lojasiewicz (KL) Property

Yingzhen Yang, Ping Li

Deep Learning From Crowdsourced Labels: Coupled Cross-Entropy Minimization, Identifiability, and Regularization

Shahana Ibrahim, Tri Nguyen, Xiao Fu

Progressive Prompts: Continual Learning for Language Models

Anastasia Razdaibiedina, Yuning Mao, Rui Hou, Madian Khabsa, Mike Lewis

GOGGLE: Generative Modelling for Tabular Data by Learning Relational Structure

Tennison Liu, Zhaozhi Qian, Jeroen Berrevoets, Mihaela van der Schaar

Interpretable Geometric Deep Learning via Learnable Randomness Injection

Siqi Miao, Yunan Luo, Mia Liu, Pan Li

How I Learned to Stop Worrying and Love Retraining

Max Zimmer, Christoph Spiegel, Sebastian Pokutta

Denoising Diffusion Samplers

Francisco Vargas, Will Sussman Grathwohl, Arnaud Doucet

Interpretations of Domain Adaptations via Layer Variational Analysis

Huan-Hsin Tseng, Hsin-Yi Lin, Kuo-Hsuan Hung, Yu Tsao

Provable Robustness against Wasserstein Distribution Shifts via Input Randomization

Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi

Empowering Graph Representation Learning with Test-Time Graph Transformation

Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang

How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study

Yiwen Kou, Zixiang Chen, Yuan Cao, Quanquan Gu

Learning Language Representations with Logical Inductive Bias

Jianshu Chen

Artificial Neuronal Ensembles with Learned Context Dependent Gating

Matthew James Tilley, Michelle Miller, David Freedman

Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation

Hong-Min Chu, Jonas Geiping, Liam H Fowl, Micah Goldblum, Tom Goldstein

Fast Sampling of Diffusion Models with Exponential Integrator

Qinsheng Zhang, Yongxin Chen

Characteristic Neural Ordinary Differential Equation

Xingzi Xu, Ali Hasan, Khalil Elkhalil, Jie Ding, Vahid Tarokh

Efficiently Controlling Multiple Risks with Pareto Testing

Bracha Laufer-Goldshtein, Adam Fisch, Regina Barzilay, Tommi S. Jaakkola

Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement

Samuel Neumann, Sungsu Lim, Ajin George Joseph, Yangchen Pan, Adam White

Learning Harmonic Molecular Representations on Riemannian Manifold

Yiqun Wang, Yuning Shen, Shi Chen, Lihao Wang, Fei Ye

Information Plane Analysis for Dropout Neural Networks

Linara Adilova, Bernhard C Geiger, Asja Fischer

TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization

Bairu Hou, Jinghan Jia, Yihua Zhang, Guanhua Zhang, Yang Zhang

Understanding Influence Functions and Datamodels via Harmonic Analysis

Nikunj Saunshi, Arushi Gupta, Mark Braverman, Sanjeev Arora