Conferences · eligible papers

ICLR

2021–2025 確定版

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Machine Learning

2023 · 1,574 papers

このEditionに反映済みのmain full research papersのみ掲載しています。著者リンクは日本の大学への著者別所属根拠がある場合に限ります。

  1. 2023 · ICLR

    Exploring Low-Rank Property in Multiple Instance Learning for Whole Slide Image Classification

    Jinxi Xiang, Jun Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  2. 2023 · ICLR

    Exploring Temporally Dynamic Data Augmentation for Video Recognition

    Taeoh Kim, Jinhyung Kim, Minho Shim, Sangdoo Yun, Myunggu Kang, Dongyoon Wee, Sangyoun Lee

    Machine Learning

    日本大学: 関与なし(対象大学)

  3. 2023 · ICLR

    Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders

    Youngwan Lee, Jeff Willette, Jonghee Kim, Juho Lee, Sung Ju Hwang

    Machine Learning

    日本大学: 関与なし(対象大学)

  4. 2023 · ICLR

    Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness

    Yuancheng Xu, Yanchao Sun, Micah Goldblum, Tom Goldstein, Furong Huang

    Machine Learning

    日本大学: 関与なし(対象大学)

  5. 2023 · ICLR

    Exploring perceptual straightness in learned visual representations

    Anne Harrington, Vasha DuTell, Ayush Tewari, Mark Hamilton, Simon Stent, Ruth Rosenholtz, William Freeman

    Machine Learning

    日本大学: 関与なし(対象大学)

  6. 2023 · ICLR

    Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping

    Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian

    Machine Learning

    日本大学: 関与なし(対象大学)

  7. 2023 · ICLR

    Exponential Generalization Bounds with Near-Optimal Rates for $L_q$-Stable Algorithms

    Xiaotong Yuan, Ping Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  8. 2023 · ICLR

    ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion

    Aleksandar Pavlović, Emanuel Sallinger

    Machine Learning

    日本大学: 関与なし(対象大学)

  9. 2023 · ICLR

    Expressive Monotonic Neural Networks

    Niklas Nolte, Ouail Kitouni, Mike Williams

    Machine Learning

    日本大学: 関与なし(対象大学)

  10. 2023 · ICLR

    Extracting Robust Models with Uncertain Examples

    Guanlin Li, Guowen Xu, Shangwei Guo, Han Qiu, Jiwei Li, Tianwei Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  11. 2023 · ICLR

    Extreme Q-Learning: MaxEnt RL without Entropy

    Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon

    Machine Learning

    日本大学: 関与なし(対象大学)

  12. 2023 · ICLR

    Extremely Simple Activation Shaping for Out-of-Distribution Detection

    Andrija Djurisic, Nebojsa Bozanic, Arjun Ashok, Rosanne Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  13. 2023 · ICLR

    FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data

    Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J Su, James Y Zou

    Machine Learning

    日本大学: 関与なし(対象大学)

  14. 2023 · ICLR

    FIGARO: Controllable Music Generation using Learned and Expert Features

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

    Machine Learning

    日本大学: 関与なし(対象大学)

  15. 2023 · ICLR

    FINDE: Neural Differential Equations for Finding and Preserving Invariant Quantities

    Takashi Matsubara, Takaharu Yaguchi

    Machine Learning

    日本大学: 神戸大学 / 大阪大学

  16. 2023 · ICLR

    FIT: A Metric for Model Sensitivity

    Ben Zandonati, Adrian Pol, Maurizio Pierini, Olya Sirkin, Tal Kopetz

    Machine Learning

    日本大学: 関与なし(対象大学)

  17. 2023 · ICLR

    FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

    Kaiyuan Zhang, Guanhong Tao, Qiuling Xu, Siyuan Cheng, Shengwei An, Yingqi Liu, Shiwei Feng, Guangyu Shen, Pin-Yu Chen, Shiqing Ma, Xiangyu Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  18. 2023 · ICLR

    Factorized Fourier Neural Operators

    Alasdair Tran, Alexander Mathews, Lexing Xie, Cheng Soon Ong

    Machine Learning

    日本大学: 関与なし(対象大学)

  19. 2023 · ICLR

    FaiREE: fair classification with finite-sample and distribution-free guarantee

    Puheng Li, James Y Zou, Linjun Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  20. 2023 · ICLR

    Fair Attribute Completion on Graph with Missing Attributes

    Dongliang Guo, Zhixuan Chu, Sheng Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  21. 2023 · ICLR

    FairGBM: Gradient Boosting with Fairness Constraints

    André F Cruz, Catarina Belém, João Bravo, Pedro Saleiro, Pedro Bizarro

    Machine Learning

    日本大学: 関与なし(対象大学)

  22. 2023 · ICLR

    Fairness and Accuracy under Domain Generalization

    Thai-Hoang Pham, Xueru Zhang, Ping Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  23. 2023 · ICLR

    Fairness-aware Contrastive Learning with Partially Annotated Sensitive Attributes

    Fengda Zhang, Kun Kuang, Long Chen, Yuxuan Liu, Chao Wu, Jun Xiao

    Machine Learning

    日本大学: 関与なし(対象大学)

  24. 2023 · ICLR

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

    Hossein Mirzaei, Mohammadreza Salehi, Sajjad Shahabi, Efstratios Gavves, Cees G Snoek, Mohammad Sabokrou, Mohammad Hossein Rohban

    Machine Learning

    日本大学: 関与なし(対象大学)

  25. 2023 · ICLR

    Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems

    Yihao Feng, Shentao Yang, Shujian Zhang, Jianguo Zhang, Caiming Xiong, Mingyuan Zhou, Huan Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  26. 2023 · ICLR

    Fast Nonlinear Vector Quantile Regression

    Aviv A. Rosenberg, Sanketh Vedula, Yaniv Romano, Alexander Bronstein

    Machine Learning

    日本大学: 関与なし(対象大学)

  27. 2023 · ICLR

    Fast Sampling of Diffusion Models with Exponential Integrator

    Qinsheng Zhang, Yongxin Chen

    Machine Learning

    日本大学: 関与なし(対象大学)

  28. 2023 · ICLR

    Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search

    Michał Zawalski, Michał Tyrolski, Konrad Czechowski, Tomasz Odrzygóźdź, Damian Stachura, Piotr Piękos, Yuhuai Wu, Łukasz Kuciński, Piotr Miłoś

    Machine Learning

    日本大学: 関与なし(対象大学)

  29. 2023 · ICLR

    FastFill: Efficient Compatible Model Update

    Florian Jaeckle, Fartash Faghri, Ali Farhadi, Oncel Tuzel, Hadi Pouransari

    Machine Learning

    日本大学: 関与なし(対象大学)

  30. 2023 · ICLR

    Faster Gradient-Free Methods for Escaping Saddle Points

    Hualin Zhang, Bin Gu

    Machine Learning

    日本大学: 関与なし(対象大学)

  31. 2023 · ICLR

    Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games

    Shicong Cen, Yuejie Chi, Simon Du, Lin Xiao

    Machine Learning

    日本大学: 関与なし(対象大学)

  32. 2023 · ICLR

    Faster federated optimization under second-order similarity

    Ahmed Khaled, Chi Jin

    Machine Learning

    日本大学: 関与なし(対象大学)

  33. 2023 · ICLR

    Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks

    Sravanti Addepalli, Anshul Hemant Nasery, Venkatesh Babu Radhakrishnan, Praneeth Netrapalli, Prateek Jain

    Machine Learning

    日本大学: 関与なし(対象大学)

  34. 2023 · ICLR

    Feature selection and low test error in shallow low-rotation ReLU networks

    Matus Telgarsky

    Machine Learning

    日本大学: 関与なし(対象大学)

  35. 2023 · ICLR

    FedDAR: Federated Domain-Aware Representation Learning

    Aoxiao Zhong, Hao He, Zhaolin Ren, Na Li, Quanzheng Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  36. 2023 · ICLR

    FedExP: Speeding Up Federated Averaging via Extrapolation

    Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi

    Machine Learning

    日本大学: 関与なし(対象大学)

  37. 2023 · ICLR

    FedFA: Federated Feature Augmentation

    Tianfei Zhou, Ender Konukoglu

    Machine Learning

    日本大学: 関与なし(対象大学)

  38. 2023 · ICLR

    FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy

    Yan Sun, Li Shen, Tiansheng Huang, Liang Ding, Dacheng Tao

    Machine Learning

    日本大学: 関与なし(対象大学)

  39. 2023 · ICLR

    Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach

    Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric Xing

    Machine Learning

    日本大学: 関与なし(対象大学)

  40. 2023 · ICLR

    Federated Learning from Small Datasets

    Michael Kamp, Jonas Fischer, Jilles Vreeken

    Machine Learning

    日本大学: 関与なし(対象大学)

  41. 2023 · ICLR

    Federated Nearest Neighbor Machine Translation

    Yichao Du, Zhirui Zhang, Bingzhe Wu, lemao liu, Tong Xu, Enhong Chen

    Machine Learning

    日本大学: 関与なし(対象大学)

  42. 2023 · ICLR

    Federated Neural Bandits

    Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet

    Machine Learning

    日本大学: 関与なし(対象大学)

  43. 2023 · ICLR

    Few-Shot Domain Adaptation For End-to-End Communication

    Jayaram Raghuram, Yijing Zeng, Dolores Garcia, Rafael Ruiz, Somesh Jha, Joerg Widmer, Suman Banerjee

    Machine Learning

    日本大学: 関与なし(対象大学)

  44. 2023 · ICLR

    Few-shot Backdoor Attacks via Neural Tangent Kernels

    Jonathan Hayase, Sewoong Oh

    Machine Learning

    日本大学: 関与なし(対象大学)

  45. 2023 · ICLR

    Few-shot Cross-domain Image Generation via Inference-time Latent-code Learning

    Arnab Mondal, Piyush Tiwary, Parag Singla, Prathosh AP

    Machine Learning

    日本大学: 関与なし(対象大学)

  46. 2023 · ICLR

    FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification

    Aliaksandra Shysheya, John Bronskill, Massimiliano Patacchiola, Sebastian Nowozin, Richard E Turner

    Machine Learning

    日本大学: 関与なし(対象大学)

  47. 2023 · ICLR

    Filter-Recovery Network for Multi-Speaker Audio-Visual Speech Separation

    Haoyue Cheng, Zhaoyang Liu, Wayne Wu, Limin Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  48. 2023 · ICLR

    Finding Actual Descent Directions for Adversarial Training

    Fabian Latorre, Igor Krawczuk, Leello Dadi, Thomas Pethick, Volkan Cevher

    Machine Learning

    日本大学: 関与なし(対象大学)

  49. 2023 · ICLR

    Finding the Global Semantic Representation in GAN through Fréchet Mean

    Jaewoong Choi, Geonho Hwang, Hyunsoo Cho, Myungjoo Kang

    Machine Learning

    日本大学: 関与なし(対象大学)

  50. 2023 · ICLR

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

    Kefan Dong, Tengyu Ma

    Machine Learning

    日本大学: 関与なし(対象大学)

  51. 2023 · ICLR

    Fisher-Legendre (FishLeg) optimization of deep neural networks

    Jezabel R. Garcia, Federica Freddi, Stathi Fotiadis, Maolin Li, Sattar Vakili, Alberto Bernacchia, Guillaume Hennequin

    Machine Learning

    日本大学: 関与なし(対象大学)

  52. 2023 · ICLR

    Flow Annealed Importance Sampling Bootstrap

    Laurence Midgley, Vincent Stimper, Gregor Simm, Bernhard Schoelkopf, José Miguel Hernández Lobato

    Machine Learning

    日本大学: 関与なし(対象大学)

  53. 2023 · ICLR

    Flow Matching for Generative Modeling

    Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, Matthew Le

    Machine Learning

    日本大学: 関与なし(対象大学)

  54. 2023 · ICLR

    Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

    Xingchao Liu, Chengyue Gong, Qiang Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  55. 2023 · ICLR

    FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation

    Zhou Xian, Bo Zhu, Zhenjia Xu, Hsiao-Yu Tung, Antonio Torralba, Katerina Fragkiadaki, Chuang Gan

    Machine Learning

    日本大学: 関与なし(対象大学)

  56. 2023 · ICLR

    FoSR: First-order spectral rewiring for addressing oversquashing in GNNs

    Kedar Karhadkar, Pradeep Banerjee, Guido Montufar

    Machine Learning

    日本大学: 関与なし(対象大学)

  57. 2023 · ICLR

    Fooling SHAP with Stealthily Biased Sampling

    Gabriel Laberge, Ulrich Aïvodji, Satoshi Hara, Mario Marchand, Foutse Khomh

    Machine Learning

    日本大学: 大阪大学

  58. 2023 · ICLR

    Formal Mathematics Statement Curriculum Learning

    Stanislas Polu, Jesse Han, Kunhao Zheng, Mantas Baksys, Igor Babuschkin, Ilya Sutskever

    Machine Learning

    日本大学: 関与なし(対象大学)

  59. 2023 · ICLR

    Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions

    Zeyuan Allen-Zhu, Yuanzhi Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  60. 2023 · ICLR

    Free Lunch for Domain Adversarial Training: Environment Label Smoothing

    YiFan Zhang, xue wang, Jian Liang, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan

    Machine Learning

    日本大学: 関与なし(対象大学)

  61. 2023 · ICLR

    FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

    Yidong Wang, Hao Chen, Qiang Heng, Wenxin Hou, Yue Fan, Zhen Wu, Jindong Wang, Marios Savvides, Takahiro Shinozaki, Bhiksha Raj, Bernt Schiele, Xing Xie

    Machine Learning

    日本大学: 東京科学大学

  62. 2023 · ICLR

    From $t$-SNE to UMAP with contrastive learning

    Sebastian Damrich, Niklas Böhm, Fred A Hamprecht, Dmitry Kobak

    Machine Learning

    日本大学: 関与なし(対象大学)

  63. 2023 · ICLR

    From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data

    Zichen Jeff Cui, Yibin Wang, Nur Muhammad Shafiullah, Lerrel Pinto

    Machine Learning

    日本大学: 関与なし(対象大学)

  64. 2023 · ICLR

    Function-Consistent Feature Distillation

    Dongyang Liu, Meina Kan, Shiguang Shan, Xilin CHEN

    Machine Learning

    日本大学: 関与なし(対象大学)

  65. 2023 · ICLR

    Function-space regularized Rényi divergences

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

    Machine Learning

    日本大学: 関与なし(対象大学)

  66. 2023 · ICLR

    Fundamental Limits in Formal Verification of Message-Passing Neural Networks

    Marco Sälzer, Martin Lange

    Machine Learning

    日本大学: 関与なし(対象大学)

  67. 2023 · ICLR

    Fundamental limits on the robustness of image classifiers

    Zheng Dai, David Gifford

    Machine Learning

    日本大学: 関与なし(対象大学)

  68. 2023 · ICLR

    FunkNN: Neural Interpolation for Functional Generation

    AmirEhsan Khorashadizadeh, Anadi Chaman, Valentin Debarnot, Ivan Dokmanic

    Machine Learning

    日本大学: 関与なし(対象大学)

  69. 2023 · ICLR

    Fuzzy Alignments in Directed Acyclic Graph for Non-Autoregressive Machine Translation

    Zhengrui Ma, Chenze Shao, Shangtong Gui, Min Zhang, Yang Feng

    Machine Learning

    日本大学: 関与なし(対象大学)

  70. 2023 · ICLR

    GAIN: On the Generalization of Instructional Action Understanding

    Junlong Li, Guangyi Chen, Yansong Tang, Jinan Bao, Kun Zhang, Jie Zhou, Jiwen Lu

    Machine Learning

    日本大学: 関与なし(対象大学)

  71. 2023 · ICLR

    GAMR: A Guided Attention Model for (visual) Reasoning

    Mohit Vaishnav, Thomas Serre

    Machine Learning

    日本大学: 関与なし(対象大学)

  72. 2023 · ICLR

    GEASS: Neural causal feature selection for high-dimensional biological data

    Mingze Dong, Yuval Kluger

    Machine Learning

    日本大学: 関与なし(対象大学)

  73. 2023 · ICLR

    GFlowNets and variational inference

    Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio

    Machine Learning

    日本大学: 関与なし(対象大学)

  74. 2023 · ICLR

    GLM-130B: An Open Bilingual Pre-trained Model

    Aohan Zeng, Xiao Liu, Zhengxiao Du, Zihan Wang, Hanyu Lai, Ming Ding, Zhuoyi Yang, Yifan Xu, Wendi Zheng, Xiao Xia, Weng Lam Tam, Zixuan Ma, Yufei Xue, Jidong Zhai, Wenguang Chen, Zhiyuan Liu, Peng Zhang, Yuxiao Dong, Jie Tang

    Machine Learning

    日本大学: 関与なし(対象大学)

  75. 2023 · ICLR

    GNNDelete: A General Strategy for Unlearning in Graph Neural Networks

    Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik

    Machine Learning

    日本大学: 関与なし(対象大学)

  76. 2023 · ICLR

    GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks

    Xiaoqi Wang, Han Wei Shen

    Machine Learning

    日本大学: 関与なし(対象大学)

  77. 2023 · ICLR

    GOGGLE: Generative Modelling for Tabular Data by Learning Relational Structure

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

    Machine Learning

    日本大学: 関与なし(対象大学)

  78. 2023 · ICLR

    GOOD: Exploring geometric cues for detecting objects in an open world

    Haiwen Huang, Andreas Geiger, Dan Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  79. 2023 · ICLR

    GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation

    Chenhongyi Yang, Jiarui Xu, Shalini De Mello, Elliot J Crowley, Xiaolong Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  80. 2023 · ICLR

    GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints

    Mohammadsajad Abavisani, David Danks, Sergey Plis

    Machine Learning

    日本大学: 関与なし(対象大学)

  81. 2023 · ICLR

    GReTo: Remedying dynamic graph topology-task discordance via target homophily

    Zhengyang Zhou, Qihe Huang, Gengyu Lin, Kuo Yang, LEI BAI, Yang Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  82. 2023 · ICLR

    GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis

    Zhenhui Ye, Ziyue Jiang, Yi Ren, Jinglin Liu, Jinzheng He, Zhou Zhao

    Machine Learning

    日本大学: 関与なし(対象大学)

  83. 2023 · ICLR

    General Neural Gauge Fields

    Fangneng Zhan, Lingjie Liu, Adam Kortylewski, Christian Theobalt

    Machine Learning

    日本大学: 関与なし(対象大学)

  84. 2023 · ICLR

    Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses

    Xiaolin Hu, Shaojie Li, Yong Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  85. 2023 · ICLR

    Generalization and Estimation Error Bounds for Model-based Neural Networks

    Avner Shultzman, Eyar Azar, Miguel Rodrigues, Yonina Eldar

    Machine Learning

    日本大学: 関与なし(対象大学)

  86. 2023 · ICLR

    Generalize Learned Heuristics to Solve Large-scale Vehicle Routing Problems in Real-time

    Qingchun Hou, Jingwei Yang, Yiqiang Su, Xiaoqing Wang, Yuming Deng

    Machine Learning

    日本大学: 関与なし(対象大学)

  87. 2023 · ICLR

    Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks

    Yujia Zheng, Ignavier Ng, Yewen Fan, Kun Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  88. 2023 · ICLR

    Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap

    Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schoelkopf

    Machine Learning

    日本大学: 関与なし(対象大学)

  89. 2023 · ICLR

    Generate rather than Retrieve: Large Language Models are Strong Context Generators

    Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, Meng Jiang

    Machine Learning

    日本大学: 関与なし(対象大学)

  90. 2023 · ICLR

    Generating Diverse Cooperative Agents by Learning Incompatible Policies

    Rujikorn Charakorn, Poramate Manoonpong, Nat Dilokthanakul

    Machine Learning

    日本大学: 関与なし(対象大学)

  91. 2023 · ICLR

    Generating Sequences by Learning to Self-Correct

    Sean Welleck, Ximing Lu, Peter West, Faeze Brahman, Tianxiao Shen, Daniel Khashabi, Yejin Choi

    Machine Learning

    日本大学: 関与なし(対象大学)

  92. 2023 · ICLR

    Generative Augmented Flow Networks

    Ling Pan, Dinghuai Zhang, Aaron Courville, Longbo Huang, Yoshua Bengio

    Machine Learning

    日本大学: 関与なし(対象大学)

  93. 2023 · ICLR

    Generative Modeling Helps Weak Supervision (and Vice Versa)

    Benedikt Boecking, Nicholas Roberts, Willie Neiswanger, Stefano Ermon, Frederic Sala, Artur Dubrawski

    Machine Learning

    日本大学: 関与なし(対象大学)

  94. 2023 · ICLR

    Generative Modelling with Inverse Heat Dissipation

    Severi Rissanen, Markus Heinonen, Arno Solin

    Machine Learning

    日本大学: 関与なし(対象大学)

  95. 2023 · ICLR

    Geometrically regularized autoencoders for non-Euclidean data

    Cheongjae Jang, Yonghyeon Lee, Yung-Kyun Noh, Frank Chongwoo Park

    Machine Learning

    日本大学: 関与なし(対象大学)

  96. 2023 · ICLR

    Git Re-Basin: Merging Models modulo Permutation Symmetries

    Samuel Ainsworth, Jonathan Hayase, Siddhartha Srinivasa

    Machine Learning

    日本大学: 関与なし(対象大学)

  97. 2023 · ICLR

    Global Explainability of GNNs via Logic Combination of Learned Concepts

    Steve Azzolin, Antonio Longa, Pietro Barbiero, Pietro Lio, Andrea Passerini

    Machine Learning

    日本大学: 関与なし(対象大学)

  98. 2023 · ICLR

    Globally Optimal Training of Neural Networks with Threshold Activation Functions

    Tolga Ergen, Halil Gulluk, Jonathan Lacotte, Mert Pilanci

    Machine Learning

    日本大学: 関与なし(対象大学)

  99. 2023 · ICLR

    GoBigger: A Scalable Platform for Cooperative-Competitive Multi-Agent Interactive Simulation

    Ming Zhang, Shenghan Zhang, Zhenjie Yang, Lekai Chen, Jinliang Zheng, yang chao, Chuming Li, Hang Zhou, Yazhe Niu, Yu Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  100. 2023 · ICLR

    Gradient Boosting Performs Gaussian Process Inference

    Aleksei Ustimenko, Artem Beliakov, Liudmila Prokhorenkova

    Machine Learning

    日本大学: 関与なし(対象大学)