ICLR 2023
1573 papers
BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion
Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Han-Jia Ye, Yatao Bian, De-Chuan Zhan, Peilin Zhao (Certified!!) Adversarial Robustness for Free!
Nicholas Carlini, Florian Tramer, Krishnamurthy Dj Dvijotham, Leslie Rice, Mingjie Sun, J Zico Kolter $\Lambda$-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection Among Cells
Sajad Movahedi, Melika Adabinejad, Ayyoob Imani, Arezou Keshavarz, Mostafa Dehghani, Azadeh Shakery, Babak N Araabi $\mathcal{O}$-GNN: Incorporating Ring Priors into Molecular Modeling
Jinhua Zhu, Kehan Wu, Bohan Wang, Yingce Xia, Shufang Xie, Qi Meng, Lijun Wu, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu $\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks
Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li, Zejian Liu, Xiaoyao Liang, Jian Cheng 3D Generation on ImageNet
Ivan Skorokhodov, Aliaksandr Siarohin, Yinghao Xu, Jian Ren, Hsin-Ying Lee, Peter Wonka, Sergey Tulyakov A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data
Jiajin Li, Jianheng Tang, Lemin Kong, Huikang Liu, Jia Li, Anthony Man-Cho So, Jose Blanchet A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming
Qingyu Han, Linxin Yang, Qian Chen, Xiang Zhou, Dong Zhang, Akang Wang, Ruoyu Sun, Xiaodong Luo A Higher Precision Algorithm for Computing the $1$-Wasserstein Distance
Pankaj K Agarwal, Sharath Raghvendra, Pouyan Shirzadian, Rachita Sowle A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond
Lin Yong, Renjie Pi, Weizhong Zhang, Xiaobo Xia, Jiahui Gao, Xiao Zhou, Tongliang Liu, Bo Han A Message Passing Perspective on Learning Dynamics of Contrastive Learning
Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang A Mixture-of-Expert Approach to RL-Based Dialogue Management
Yinlam Chow, Azamat Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier A Primal-Dual Framework for Transformers and Neural Networks
Tan Minh Nguyen, Tam Minh Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard Baraniuk, Stanley Osher A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search
Brandon Trabucco, Gunnar A Sigurdsson, Robinson Piramuthu, Gaurav S. Sukhatme, Ruslan Salakhutdinov A Theoretical Framework for Inference and Learning in Predictive Coding Networks
Beren Millidge, Yuhang Song, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz A Theory of Dynamic Benchmarks
Ali Shirali, Rediet Abebe, Moritz Hardt A Unified Algebraic Perspective on Lipschitz Neural Networks
Alexandre Araujo, Aaron J Havens, Blaise Delattre, Alexandre Allauzen, Bin Hu A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games
Samuel Sokota, Ryan D'Orazio, J Zico Kolter, Nicolas Loizou, Marc Lanctot, Ioannis Mitliagkas, Noam Brown, Christian Kroer A Unified Framework for Soft Threshold Pruning
Yanqi Chen, Zhengyu Ma, Wei Fang, Xiawu Zheng, Zhaofei Yu, Yonghong Tian A View from Somewhere: Human-Centric Face Representations
Jerone Theodore Alexander Andrews, Przemyslaw Joniak, Alice Xiang AANG : Automating Auxiliary Learning
Lucio M. Dery, Paul Michel, Mikhail Khodak, Graham Neubig, Ameet Talwalkar Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference
Michael Volpp, Philipp Dahlinger, Philipp Becker, Christian Daniel, Gerhard Neumann Accurate Image Restoration with Attention Retractable Transformer
Jiale Zhang, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan Achieving Near-Optimal Individual Regret & Low Communications in Multi-Agent Bandits
Xuchuang Wang, Lin Yang, Yu-Zhen Janice Chen, Xutong Liu, Mohammad Hajiesmaili, Don Towsley, John C.S. Lui Actionable Neural Representations: Grid Cells from Minimal Constraints
Will Dorrell, Peter E. Latham, Timothy E. J. Behrens, James C. R. Whittington Active Image Indexing
Pierre Fernandez, Matthijs Douze, Herve Jegou, Teddy Furon Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation
Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber, Hamid Eghbal-zadeh, Bernhard A. Moser, Sergei Pereverzyev, Sepp Hochreiter, Werner Zellinger Adversarial Diversity in Hanabi
Brandon Cui, Andrei Lupu, Samuel Sokota, Hengyuan Hu, David J Wu, Jakob Nicolaus Foerster Adversarial Imitation Learning with Preferences
Aleksandar Taranovic, Andras Gabor Kupcsik, Niklas Freymuth, Gerhard Neumann Agent-Based Graph Neural Networks
Karolis Martinkus, Pál András Papp, Benedikt Schesch, Roger Wattenhofer Agree to Disagree: Diversity Through Disagreement for Better Transferability
Matteo Pagliardini, Martin Jaggi, François Fleuret, Sai Praneeth Karimireddy AGRO: Adversarial Discovery of Error-Prone Groups for Robust Optimization
Bhargavi Paranjape, Pradeep Dasigi, Vivek Srikumar, Luke Zettlemoyer, Hannaneh Hajishirzi AIM: Adapting Image Models for Efficient Video Action Recognition
Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, Mu Li Alternating Differentiation for Optimization Layers
Haixiang Sun, Ye Shi, Jingya Wang, Hoang Duong Tuan, H. Vincent Poor, Dacheng Tao Amortised Invariance Learning for Contrastive Self-Supervision
Ruchika Chavhan, Jan Stuehmer, Calum Heggan, Mehrdad Yaghoobi, Timothy Hospedales An Additive Instance-Wise Approach to Multi-Class Model Interpretation
Vy Vo, Van Nguyen, Trung Le, Quan Hung Tran, Gholamreza Haffari, Seyit Camtepe, Dinh Phung An Extensible Multi-Modal Multi-Task Object Dataset with Materials
Trevor Scott Standley, Ruohan Gao, Dawn Chen, Jiajun Wu, Silvio Savarese An Image Is Worth One Word: Personalizing Text-to-Image Generation Using Textual Inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit Haim Bermano, Gal Chechik, Daniel Cohen-Or Analogy-Forming Transformers for Few-Shot 3D Parsing
Nikolaos Gkanatsios, Mayank Singh, Zhaoyuan Fang, Shubham Tulsiani, Katerina Fragkiadaki Any-Scale Balanced Samplers for Discrete Space
Haoran Sun, Bo Dai, Charles Sutton, Dale Schuurmans, Hanjun Dai AnyDA: Anytime Domain Adaptation
Omprakash Chakraborty, Aadarsh Sahoo, Rameswar Panda, Abir Das Approximate Vanishing Ideal Computations at Scale
Elias Samuel Wirth, Hiroshi Kera, Sebastian Pokutta Are More Layers Beneficial to Graph Transformers?
Haiteng Zhao, Shuming Ma, Dongdong Zhang, Zhi-Hong Deng, Furu Wei Ask Me Anything: A Simple Strategy for Prompting Language Models
Simran Arora, Avanika Narayan, Mayee F Chen, Laurel Orr, Neel Guha, Kush Bhatia, Ines Chami, Christopher Re Asynchronous Distributed Bilevel Optimization
Yang Jiao, Kai Yang, Tiancheng Wu, Dongjin Song, Chengtao Jian AudioGen: Textually Guided Audio Generation
Felix Kreuk, Gabriel Synnaeve, Adam Polyak, Uriel Singer, Alexandre Défossez, Jade Copet, Devi Parikh, Yaniv Taigman, Yossi Adi Auto-Encoding Goodness of Fit
Aaron Palmer, Zhiyi Chi, Derek Aguiar, Jinbo Bi AutoGT: Automated Graph Transformer Architecture Search
Zizhao Zhang, Xin Wang, Chaoyu Guan, Ziwei Zhang, Haoyang Li, Wenwu Zhu Automated Data Augmentations for Graph Classification
Youzhi Luo, Michael Curtis McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji Autoregressive Conditional Neural Processes
Wessel Bruinsma, Stratis Markou, James Requeima, Andrew Y. K. Foong, Tom Andersson, Anna Vaughan, Anthony Buonomo, Scott Hosking, Richard E Turner Avoiding Spurious Correlations via Logit Correction
Sheng Liu, Xu Zhang, Nitesh Sekhar, Yue Wu, Prateek Singhal, Carlos Fernandez-Granda Backpropagation Through Combinatorial Algorithms: Identity with Projection Works
Subham Sekhar Sahoo, Anselm Paulus, Marin Vlastelica, Vít Musil, Volodymyr Kuleshov, Georg Martius BALTO: Fast Tensor Program Optimization with Diversity-Based Active Learning
Jun Bi, Xiaqing Li, Qi Guo, Rui Zhang, Yuanbo Wen, Xing Hu, Zidong Du, Xinkai Song, Yifan Hao, Yunji Chen Basic Binary Convolution Unit for Binarized Image Restoration Network
Bin Xia, Yulun Zhang, Yitong Wang, Yapeng Tian, Wenming Yang, Radu Timofte, Luc Van Gool Batch Multivalid Conformal Prediction
Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth Bayes Risk Ctc: Controllable Ctc Alignment in Sequence-to-Sequence Tasks
Jinchuan Tian, Brian Yan, Jianwei Yu, Chao Weng, Dong Yu, Shinji Watanabe Bayesian Oracle for Bounding Information Gain in Neural Encoding Models
Konstantin-Klemens Lurz, Mohammad Bashiri, Edgar Y. Walker, Fabian H. Sinz Behavior Prior Representation Learning for Offline Reinforcement Learning
Hongyu Zang, Xin Li, Jie Yu, Chen Liu, Riashat Islam, Remi Tachet des Combes, Romain Laroche Behavior Proximal Policy Optimization
Zifeng Zhuang, Kun Lei, Jinxin Liu, Donglin Wang, Yilang Guo Benchmarking Constraint Inference in Inverse Reinforcement Learning
Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart Benchmarking Offline Reinforcement Learning on Real-Robot Hardware
Nico Gürtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier, Manuel Wuthrich, Stefan Bauer, Bernhard Schölkopf, Georg Martius Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge Distillation
Martin Zong, Zengyu Qiu, Xinzhu Ma, Kunlin Yang, Chunya Liu, Jun Hou, Shuai Yi, Wanli Ouyang BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection
Zehui Chen, Zhenyu Li, Shiquan Zhang, Liangji Fang, Qinhong Jiang, Feng Zhao Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD
Konstantinos Nikolakakis, Farzin Haddadpour, Amin Karbasi, Dionysios Kalogerias Bidirectional Language Models Are Also Few-Shot Learners
Ajay Patel, Bryan Li, Mohammad Sadegh Rasooli, Noah Constant, Colin Raffel, Chris Callison-Burch BigVGAN: A Universal Neural Vocoder with Large-Scale Training
Sang-gil Lee, Wei Ping, Boris Ginsburg, Bryan Catanzaro, Sungroh Yoon Binding Language Models in Symbolic Languages
Zhoujun Cheng, Tianbao Xie, Peng Shi, Chengzu Li, Rahul Nadkarni, Yushi Hu, Caiming Xiong, Dragomir Radev, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Tao Yu Bispectral Neural Networks
Sophia Sanborn, Christian A Shewmake, Bruno Olshausen, Christopher J. Hillar Bitrate-Constrained DRO: Beyond Worst Case Robustness to Unknown Group Shifts
Amrith Setlur, Don Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine Blurring Diffusion Models
Emiel Hoogeboom, Tim Salimans Boosting Adversarial Transferability Using Dynamic Cues
Muzammal Naseer, Ahmad Mahmood, Salman Khan, Fahad Khan Boosting Causal Discovery via Adaptive Sample Reweighting
An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang, Tat-Seng Chua BrainBERT: Self-Supervised Representation Learning for Intracranial Recordings
Christopher Wang, Vighnesh Subramaniam, Adam Uri Yaari, Gabriel Kreiman, Boris Katz, Ignacio Cases, Andrei Barbu Bridging the Gap to Real-World Object-Centric Learning
Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello Broken Neural Scaling Laws
Ethan Caballero, Kshitij Gupta, Irina Rish, David Krueger Budgeted Training for Vision Transformer
Zhuofan Xia, Xuran Pan, Xuan Jin, Yuan He, Hui Xue', Shiji Song, Gao Huang Building a Subspace of Policies for Scalable Continual Learning
Jean-Baptiste Gaya, Thang Doan, Lucas Caccia, Laure Soulier, Ludovic Denoyer, Roberta Raileanu Calibrating Sequence Likelihood Improves Conditional Language Generation
Yao Zhao, Mikhail Khalman, Rishabh Joshi, Shashi Narayan, Mohammad Saleh, Peter J Liu Can CNNs Be More Robust than Transformers?
Zeyu Wang, Yutong Bai, Yuyin Zhou, Cihang Xie Can Discrete Information Extraction Prompts Generalize Across Language Models?
Nathanaël Carraz Rakotonirina, Roberto Dessi, Fabio Petroni, Sebastian Riedel, Marco Baroni Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries
Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein Causal Balancing for Domain Generalization
Xinyi Wang, Michael Saxon, Jiachen Li, Hongyang Zhang, Kun Zhang, William Yang Wang Certifiably Robust Policy Learning Against Adversarial Multi-Agent Communication
Yanchao Sun, Ruijie Zheng, Parisa Hassanzadeh, Yongyuan Liang, Soheil Feizi, Sumitra Ganesh, Furong Huang Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation
Maksym Yatsura, Kaspar Sakmann, N. Grace Hua, Matthias Hein, Jan Hendrik Metzen Certified Training: Small Boxes Are All You Need
Mark Niklas Mueller, Franziska Eckert, Marc Fischer, Martin Vechev Characteristic Neural Ordinary Differential Equation
Xingzi Xu, Ali Hasan, Khalil Elkhalil, Jie Ding, Vahid Tarokh Characterizing the Influence of Graph Elements
Zizhang Chen, Peizhao Li, Hongfu Liu, Pengyu Hong Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization
Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh Chawla, Chuxu Zhang Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning
Yat Long Lo, Christian Schroeder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson ChiroDiff: Modelling Chirographic Data with Diffusion Models
Ayan Das, Yongxin Yang, Timothy Hospedales, Tao Xiang, Yi-Zhe Song Choreographer: Learning and Adapting Skills in Imagination
Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar CktGNN: Circuit Graph Neural Network for Electronic Design Automation
Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang Clifford Neural Layers for PDE Modeling
Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K Gupta CLIP-ViP: Adapting Pre-Trained Image-Text Model to Video-Language Alignment
Hongwei Xue, Yuchong Sun, Bei Liu, Jianlong Fu, Ruihua Song, Houqiang Li, Jiebo Luo CLIPSep: Learning Text-Queried Sound Separation with Noisy Unlabeled Videos
Hao-Wen Dong, Naoya Takahashi, Yuki Mitsufuji, Julian McAuley, Taylor Berg-Kirkpatrick CO3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving
Runjian Chen, Yao Mu, Runsen Xu, Wenqi Shao, Chenhan Jiang, Hang Xu, Yu Qiao, Zhenguo Li, Ping Luo Code Translation with Compiler Representations
Marc Szafraniec, Baptiste Roziere, Hugh James Leather, Patrick Labatut, Francois Charton, Gabriel Synnaeve CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, Caiming Xiong CodeT: Code Generation with Generated Tests
Bei Chen, Fengji Zhang, Anh Nguyen, Daoguang Zan, Zeqi Lin, Jian-Guang Lou, Weizhu Chen Combating Exacerbated Heterogeneity for Robust Models in Federated Learning
Jianing Zhu, Jiangchao Yao, Tongliang Liu, Quanming Yao, Jianliang Xu, Bo Han Competitive Physics Informed Networks
Qi Zeng, Yash Kothari, Spencer H Bryngelson, Florian Tobias Schaefer Complexity-Based Prompting for Multi-Step Reasoning
Yao Fu, Hao Peng, Ashish Sabharwal, Peter Clark, Tushar Khot Composing Ensembles of Pre-Trained Models via Iterative Consensus
Shuang Li, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba, Igor Mordatch Composing Task Knowledge with Modular Successor Feature Approximators
Wilka Torrico Carvalho, Angelos Filos, Richard Lewis, Honglak Lee, Satinder Singh Composite Slice Transformer: An Efficient Transformer with Composition of Multi-Scale Multi-Range Attentions
Mingu Lee, Saurabh Pitre, Tianyu Jiang, Pierre-David Letourneau, Matthew J Morse, Kanghwan Jang, Joseph Soriaga, Parham Noorzad, Hsin-Pai Cheng, Christopher Lott Compositional Semantic Parsing with Large Language Models
Andrew Drozdov, Nathanael Schärli, Ekin Akyürek, Nathan Scales, Xinying Song, Xinyun Chen, Olivier Bousquet, Denny Zhou Compositional Task Representations for Large Language Models
Nan Shao, Zefan Cai, Hanwei Xu, Chonghua Liao, Yanan Zheng, Zhilin Yang Computational Language Acquisition with Theory of Mind
Andy Liu, Hao Zhu, Emmy Liu, Yonatan Bisk, Graham Neubig Computing All Optimal Partial Transports
Abhijeet Phatak, Sharath Raghvendra, Chittaranjan Tripathy, Kaiyi Zhang Concept Gradient: Concept-Based Interpretation Without Linear Assumption
Andrew Bai, Chih-Kuan Yeh, Neil Y.C. Lin, Pradeep Kumar Ravikumar, Cho-Jui Hsieh Concept-Level Debugging of Part-Prototype Networks
Andrea Bontempelli, Stefano Teso, Katya Tentori, Fausto Giunchiglia, Andrea Passerini Conditional Positional Encodings for Vision Transformers
Xiangxiang Chu, Zhi Tian, Bo Zhang, Xinlong Wang, Chunhua Shen Confidential-PROFITT: Confidential PROof of FaIr Training of Trees
Ali Shahin Shamsabadi, Sierra Calanda Wyllie, Nicholas Franzese, Natalie Dullerud, Sébastien Gambs, Nicolas Papernot, Xiao Wang, Adrian Weller Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization
Jihwan Jeong, Xiaoyu Wang, Michael Gimelfarb, Hyunwoo Kim, Baher Abdulhai, Scott Sanner Constraining Representations Yields Models That Know What They Don't Know
Joao Monteiro, Pau Rodriguez, Pierre-Andre Noel, Issam H. Laradji, David Vazquez Context-Enriched Molecule Representations Improve Few-Shot Drug Discovery
Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann, Sepp Hochreiter, Günter Klambauer Contextual Bandits with Concave Rewards, and an Application to Fair Ranking
Virginie Do, Elvis Dohmatob, Matteo Pirotta, Alessandro Lazaric, Nicolas Usunier Contextual Convolutional Networks
Shuxian Liang, Xu Shen, Tongliang Liu, Xian-Sheng Hua Continual Pre-Training of Language Models
Zixuan Ke, Yijia Shao, Haowei Lin, Tatsuya Konishi, Gyuhak Kim, Bing Liu Continual Unsupervised Disentangling of Self-Organizing Representations
Zhiyuan Li, Xiajun Jiang, Ryan Missel, Prashnna Kumar Gyawali, Nilesh Kumar, Linwei Wang Continuous PDE Dynamics Forecasting with Implicit Neural Representations
Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari Continuous Pseudo-Labeling from the Start
Dan Berrebbi, Ronan Collobert, Samy Bengio, Navdeep Jaitly, Tatiana Likhomanenko Contrastive Audio-Visual Masked Autoencoder
Yuan Gong, Andrew Rouditchenko, Alexander H. Liu, David Harwath, Leonid Karlinsky, Hilde Kuehne, James R. Glass Copy Is All You Need
Tian Lan, Deng Cai, Yan Wang, Heyan Huang, Xian-Ling Mao CoRTX: Contrastive Framework for Real-Time Explanation
Yu-Neng Chuang, Guanchu Wang, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Hu Coupled Multiwavelet Operator Learning for Coupled Differential Equations
Xiongye Xiao, Defu Cao, Ruochen Yang, Gaurav Gupta, Gengshuo Liu, Chenzhong Yin, Radu Balan, Paul Bogdan CrAM: A Compression-Aware Minimizer
Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H Lampert, Dan Alistarh Critic Sequential Monte Carlo
Vasileios Lioutas, Jonathan Wilder Lavington, Justice Sefas, Matthew Niedoba, Yunpeng Liu, Berend Zwartsenberg, Setareh Dabiri, Frank Wood, Adam Scibior CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations
Peter Yichen Chen, Jinxu Xiang, Dong Heon Cho, Yue Chang, G A Pershing, Henrique Teles Maia, Maurizio M Chiaramonte, Kevin Thomas Carlberg, Eitan Grinspun Cross-Layer Retrospective Retrieving via Layer Attention
Yanwen Fang, Yuxi Cai, Jintai Chen, Jingyu Zhao, Guangjian Tian, Guodong Li Curriculum-Based Co-Design of Morphology and Control of Voxel-Based Soft Robots
Yuxing Wang, Shuang Wu, Haobo Fu, Qiang Fu, Tiantian Zhang, Yongzhe Chang, Xueqian Wang CUTS: Neural Causal Discovery from Irregular Time-Series Data
Yuxiao Cheng, Runzhao Yang, Tingxiong Xiao, Zongren Li, Jinli Suo, Kunlun He, Qionghai Dai Cycle-Consistent Masked AutoEncoder for Unsupervised Domain Generalization
Haiyang Yang, Xiaotong Li, Shixiang Tang, Feng Zhu, Yizhou Wang, Meilin Chen, Lei Bai, Rui Zhao, Wanli Ouyang D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory
Tianbo Li, Min Lin, Zheyuan Hu, Kunhao Zheng, Giovanni Vignale, Kenji Kawaguchi, A.H. Castro Neto, Kostya S. Novoselov, Shuicheng Yan DAG Learning on the Permutahedron
Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt Kusner, Vlad Niculae DamoFD: Digging into Backbone Design on Face Detection
Yang Liu, Jiankang Deng, Fei Wang, Lei Shang, Xuansong Xie, Baigui Sun DBQ-SSD: Dynamic Ball Query for Efficient 3D Object Detection
Jinrong Yang, Lin Song, Songtao Liu, Weixin Mao, Zeming Li, Xiaoping Li, Hongbin Sun, Jian Sun, Nanning Zheng DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability
Cian Eastwood, Andrei Liviu Nicolicioiu, Julius Von Kügelgen, Armin Kekić, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf De Novo Molecular Generation via Connection-Aware Motif Mining
Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases
Donghan Yu, Sheng Zhang, Patrick Ng, Henghui Zhu, Alexander Hanbo Li, Jun Wang, Yiqun Hu, William Yang Wang, Zhiguo Wang, Bing Xiang Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models
Liam H Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojciech Czaja, Micah Goldblum, Tom Goldstein Decomposed Prompting: A Modular Approach for Solving Complex Tasks
Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal Deconstructing Distributions: A Pointwise Framework of Learning
Gal Kaplun, Nikhil Ghosh, Saurabh Garg, Boaz Barak, Preetum Nakkiran Deep Ensembles for Graphs with Higher-Order Dependencies
Steven Krieg, William Burgis, Patrick Soga, Nitesh Chawla Deep Generative Symbolic Regression
Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar Deep Learning on Implicit Neural Representations of Shapes
Luca De Luigi, Adriano Cardace, Riccardo Spezialetti, Pierluigi Zama Ramirez, Samuele Salti, Luigi di Stefano Deep Ranking Ensembles for Hyperparameter Optimization
Abdus Salam Khazi, Sebastian Pineda Arango, Josif Grabocka Deep Reinforcement Learning for Cost-Effective Medical Diagnosis
Zheng Yu, Yikuan Li, Joseph Chahn Kim, Kaixuan Huang, Yuan Luo, Mengdi Wang Deep Transformers Without Shortcuts: Modifying Self-Attention for Faithful Signal Propagation
Bobby He, James Martens, Guodong Zhang, Aleksandar Botev, Andrew Brock, Samuel L Smith, Yee Whye Teh Deep Variational Implicit Processes
Luis A. Ortega, Simon Rodriguez Santana, Daniel Hernández-Lobato Defending Against Adversarial Audio via Diffusion Model
Shutong Wu, Jiongxiao Wang, Wei Ping, Weili Nie, Chaowei Xiao Deja Vu: Continual Model Generalization for Unseen Domains
Chenxi Liu, Lixu Wang, Lingjuan Lyu, Chen Sun, Xiao Wang, Qi Zhu Delving into Semantic Scale Imbalance
Yanbiao Ma, Licheng Jiao, Fang Liu, Yuxin Li, Shuyuan Yang, Xu Liu Denoising Diffusion Samplers
Francisco Vargas, Will Sussman Grathwohl, Arnaud Doucet Denoising Masked Autoencoders Help Robust Classification
QuanLin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He Dense RGB SLAM with Neural Implicit Maps
Heng Li, Xiaodong Gu, Weihao Yuan, Luwei Yang, Zilong Dong, Ping Tan DensePure: Understanding Diffusion Models for Adversarial Robustness
Chaowei Xiao, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song Diagnosing and Rectifying Vision Models Using Language
Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola Differentially Private Adaptive Optimization with Delayed Preconditioners
Tian Li, Manzil Zaheer, Ken Liu, Sashank J. Reddi, Hugh Brendan McMahan, Virginia Smith DiffMimic: Efficient Motion Mimicking with Differentiable Physics
Jiawei Ren, Cunjun Yu, Siwei Chen, Xiao Ma, Liang Pan, Ziwei Liu DiffusER: Diffusion via Edit-Based Reconstruction
Machel Reid, Vincent Josua Hellendoorn, Graham Neubig Diffusion Models for Causal Discovery via Topological Ordering
Pedro Sanchez, Xiao Liu, Alison Q O'Neil, Sotirios A. Tsaftaris Diffusion Posterior Sampling for General Noisy Inverse Problems
Hyungjin Chung, Jeongsol Kim, Michael Thompson Mccann, Marc Louis Klasky, Jong Chul Ye Diffusion Probabilistic Fields
Peiye Zhuang, Samira Abnar, Jiatao Gu, Alex Schwing, Joshua M. Susskind, Miguel Ángel Bautista Diffusion Probabilistic Modeling of Protein Backbones in 3D for the Motif-Scaffolding Problem
Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi S. Jaakkola Diffusion-GAN: Training GANs with Diffusion
Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou DiGress: Discrete Denoising Diffusion for Graph Generation
Clement Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard Dilated Convolution with Learnable Spacings
Ismail Khalfaoui Hassani, Thomas Pellegrini, Timothée Masquelier DINO as a Von Mises-Fisher Mixture Model
Hariprasath Govindarajan, Per Sidén, Jacob Roll, Fredrik Lindsten DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
Hao Zhang, Feng Li, Shilong Liu, Lei Zhang, Hang Su, Jun Zhu, Lionel Ni, Heung-Yeung Shum Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs
Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron N Musco Discovering Evolution Strategies via Meta-Black-Box Optimization
Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag Discovering Policies with DOMiNO: Diversity Optimization Maintaining near Optimality
Tom Zahavy, Yannick Schroecker, Feryal Behbahani, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Singh Discrete Predictor-Corrector Diffusion Models for Image Synthesis
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Michael Chang, Alyssa Li Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang Hierarchical Sliced Wasserstein Distance
Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Minh Nguyen, Nhat Ho HiViT: A Simpler and More Efficient Design of Hierarchical Vision Transformer
Xiaosong Zhang, Yunjie Tian, Lingxi Xie, Wei Huang, Qi Dai, Qixiang Ye, Qi Tian HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing
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Arna Ghosh, Yuhan Helena Liu, Guillaume Lajoie, Konrad Kording, Blake Aaron Richards How to Prepare Your Task Head for Finetuning
Yi Ren, Shangmin Guo, Wonho Bae, Danica J. Sutherland Human Alignment of Neural Network Representations
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Guy Tevet, Sigal Raab, Brian Gordon, Yoni Shafir, Daniel Cohen-Or, Amit Haim Bermano Human MotionFormer: Transferring Human Motions with Vision Transformers
Hongyu Liu, Xintong Han, Chenbin Jin, Lihui Qian, Huawei Wei, Zhe Lin, Faqiang Wang, Haoye Dong, Yibing Song, Jia Xu, Qifeng Chen Human-Guided Fair Classification for Natural Language Processing
Florian E. Dorner, Momchil Peychev, Nikola Konstantinov, Naman Goel, Elliott Ash, Martin Vechev Human-Level Atari 200x Faster
Steven Kapturowski, Víctor Campos, Ray Jiang, Nemanja Rakicevic, Hado van Hasselt, Charles Blundell, Adria Puigdomenech Badia Humanly Certifying Superhuman Classifiers
Qiongkai Xu, Christian Walder, Chenchen Xu Hungry Hungry Hippos: Towards Language Modeling with State Space Models
Daniel Y Fu, Tri Dao, Khaled Kamal Saab, Armin W Thomas, Atri Rudra, Christopher Re Hybrid RL: Using Both Offline and Online Data Can Make RL Efficient
Yuda Song, Yifei Zhou, Ayush Sekhari, Drew Bagnell, Akshay Krishnamurthy, Wen Sun Hyper-Decision Transformer for Efficient Online Policy Adaptation
Mengdi Xu, Yuchen Lu, Yikang Shen, Shun Zhang, Ding Zhao, Chuang Gan HypeR: Multitask Hyper-Prompted Training Enables Large-Scale Retrieval Generalization
ZeFeng Cai, Chongyang Tao, Tao Shen, Can Xu, Xiubo Geng, Xin Alex Lin, Liang He, Daxin Jiang Hyperbolic Deep Reinforcement Learning
Edoardo Cetin, Benjamin Paul Chamberlain, Michael M. Bronstein, Jonathan J Hunt Identifiability Results for Multimodal Contrastive Learning
Imant Daunhawer, Alice Bizeul, Emanuele Palumbo, Alexander Marx, Julia E Vogt Image as Set of Points
Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun, Chang Liu, Yun Fu ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations
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Junsu Kim, Younggyo Seo, Sungsoo Ahn, Kyunghwan Son, Jinwoo Shin Imitating Human Behaviour with Diffusion Models
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Jiangyuan Li, Thanh V Nguyen, Chinmay Hegde, Raymond K. W. Wong Impossibly Good Experts and How to Follow Them
Aaron Walsman, Muru Zhang, Sanjiban Choudhury, Dieter Fox, Ali Farhadi Improving Deep Regression with Ordinal Entropy
Shihao Zhang, Linlin Yang, Michael Bi Mi, Xiaoxu Zheng, Angela Yao In-Context Reinforcement Learning with Algorithm Distillation
Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, Dj Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih In-Sample Actor Critic for Offline Reinforcement Learning
Hongchang Zhang, Yixiu Mao, Boyuan Wang, Shuncheng He, Yi Xu, Xiangyang Ji InCoder: A Generative Model for Code Infilling and Synthesis
Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Scott Yih, Luke Zettlemoyer, Mike Lewis Information-Theoretic Diffusion
Xianghao Kong, Rob Brekelmans, Greg Ver Steeg Interactive Portrait Harmonization
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Adrien Ali Taiga, Rishabh Agarwal, Jesse Farebrother, Aaron Courville, Marc G Bellemare Is a Caption Worth a Thousand Images? a Study on Representation Learning
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Ruifei He, Shuyang Sun, Xin Yu, Chuhui Xue, Wenqing Zhang, Philip Torr, Song Bai, Xiaojuan Qi ISAAC Newton: Input-Based Approximate Curvature for Newton's Method
Felix Petersen, Tobias Sutter, Christian Borgelt, Dongsung Huh, Hilde Kuehne, Yuekai Sun, Oliver Deussen Iterative Circuit Repair Against Formal Specifications
Matthias Cosler, Frederik Schmitt, Christopher Hahn, Bernd Finkbeiner Jointly Learning Visual and Auditory Speech Representations from Raw Data
Alexandros Haliassos, Pingchuan Ma, Rodrigo Mira, Stavros Petridis, Maja Pantic Kernel Neural Optimal Transport
Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev kNN-Diffusion: Image Generation via Large-Scale Retrieval
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Rattana Pukdee, Dylan Sam, Pradeep Kumar Ravikumar, Nina Balcan Label-Free Concept Bottleneck Models
Tuomas Oikarinen, Subhro Das, Lam M. Nguyen, Tsui-Wei Weng Language Modelling with Pixels
Phillip Rust, Jonas F. Lotz, Emanuele Bugliarello, Elizabeth Salesky, Miryam de Lhoneux, Desmond Elliott Language Models Are Multilingual Chain-of-Thought Reasoners
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Vadim Borisov, Kathrin Sessler, Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci Large Language Models Are Human-Level Prompt Engineers
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba Latent Bottlenecked Attentive Neural Processes
Leo Feng, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed Latent Graph Inference Using Product Manifolds
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Valerii Iakovlev, Cagatay Yildiz, Markus Heinonen, Harri Lähdesmäki Latent State Marginalization as a Low-Cost Approach for Improving Exploration
Dinghuai Zhang, Aaron Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen Latent Variable Representation for Reinforcement Learning
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Hoang Anh Just, Feiyang Kang, Tianhao Wang, Yi Zeng, Myeongseob Ko, Ming Jin, Ruoxi Jia Learnable Behavior Control: Breaking Atari Human World Records via Sample-Efficient Behavior Selection
Jiajun Fan, Yuzheng Zhuang, Yuecheng Liu, Jianye Hao, Bin Wang, Jiangcheng Zhu, Hao Wang, Shu-Tao Xia Learnable Graph Convolutional Attention Networks
Adrián Javaloy, Pablo Sanchez Martin, Amit Levi, Isabel Valera Learned Index with Dynamic $\epsilon$
Daoyuan Chen, Wuchao Li, Yaliang Li, Bolin Ding, Kai Zeng, Defu Lian, Jingren Zhou Learning About Progress from Experts
Jake Bruce, Ankit Anand, Bogdan Mazoure, Rob Fergus Learning Controllable Adaptive Simulation for Multi-Resolution Physics
Tailin Wu, Takashi Maruyama, Qingqing Zhao, Gordon Wetzstein, Jure Leskovec Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model
Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu Learning Domain-Agnostic Representation for Disease Diagnosis
Churan Wang, Jing Li, Xinwei Sun, Fandong Zhang, Yizhou Yu, Yizhou Wang Learning in Temporally Structured Environments
Matt Jones, Tyler R. Scott, Mengye Ren, Gamaleldin Fathy Elsayed, Katherine Hermann, David Mayo, Michael Curtis Mozer Learning Locality and Isotropy in Dialogue Modeling
Han Wu, Haochen Tan, Mingjie Zhan, Gangming Zhao, Shaoqing Lu, Ding Liang, Linqi Song Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets
Edo Cohen-Karlik, Itamar Menuhin-Gruman, Raja Giryes, Nadav Cohen, Amir Globerson Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions
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