ICML

2021–2025 確定版

著者一覧 · 国際会議 · 大学ランキング

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Machine Learning

2024 · 2,610 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。

2024 · ICML
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
Langzhang Liang, Sunwoo Kim, Kijung Shin, Zenglin Xu, Shirui Pan, Yuan Qi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding
Chanho Park, Namyoon Lee
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SimPro: A Simple Probabilistic Framework Towards Realistic Long-Tailed Semi-Supervised Learning
Chaoqun Du, Yizeng Han, Gao Huang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Simple Ingredients for Offline Reinforcement Learning
Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Simple linear attention language models balance the recall-throughput tradeoff
Simran Arora, Sabri Eyuboglu, Michael Zhang, Aman Timalsina, Silas Alberti, James Zou, Atri Rudra, Christopher Re
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data
Nikita Tsoy, Nikola Konstantinov
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Simplicity Bias via Global Convergence of Sharpness Minimization
Khashayar Gatmiry, Zhiyuan Li, Sashank J. Reddi, Stefanie Jegelka
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Simulation of Graph Algorithms with Looped Transformers
Artur Back De Luca, Kimon Fountoulakis
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Simulation-Based Inference with Quantile Regression
He Jia
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Simultaneous identification of models and parameters of scientific simulators
Cornelius Schröder, Jakob H. Macke
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Single-Model Attribution of Generative Models Through Final-Layer Inversion
Mike Laszkiewicz, Jonas Ricker, Johannes Lederer, Asja Fischer
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Single-Trajectory Distributionally Robust Reinforcement Learning
Zhipeng Liang, Xiaoteng Ma, Jose Blanchet, Jun Yang, Jiheng Zhang, Zhengyuan Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection
Feiran Li, Qianqian Xu, Shilong Bao, Zhiyong Yang, Runmin Cong, Xiaochun Cao, Qingming Huang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
Kolby Nottingham, Bodhisattwa Prasad Majumder, Bhavana Dalvi Mishra, Sameer Singh, Peter Clark, Roy Fox
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals
Rahul Thapa, Bryan He, Magnus Ruud Kjaer, Hyatt Moore Iv, Gauri Ganjoo, Emmanuel Mignot, James Zou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sliced Wasserstein with Random-Path Projecting Directions
Khai Nguyen, Shujian Zhang, Tam Le, Nhat Ho
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates
Rémi Leluc, Aymeric Dieuleveut, François Portier, Johan Segers, Aigerim Zhuman
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Slicedit: Zero-Shot Video Editing With Text-to-Image Diffusion Models Using Spatio-Temporal Slices
Nathaniel Cohen, Vladimir Kulikov, Matan Kleiner, Inbar Huberman-Spiegelglas, Tomer Michaeli
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Slicing Mutual Information Generalization Bounds for Neural Networks
Kimia Nadjahi, Kristjan Greenewald, Rickard Brüel Gabrielsson, Justin Solomon
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sliding Down the Stairs: How Correlated Latent Variables Accelerate Learning with Neural Networks
Lorenzo Bardone, Sebastian Goldt
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Slot Abstractors: Toward Scalable Abstract Visual Reasoning
Shanka Subhra Mondal, Jonathan D. Cohen, Taylor Whittington Webb
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks
Hojoon Lee, Hyeonseo Cho, Hyunseung Kim, Donghu Kim, Dugki Min, Jaegul Choo, Clare Lyle
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Small-loss Adaptive Regret for Online Convex Optimization
Wenhao Yang, Wei Jiang, Yibo Wang, Ping Yang, Yao Hu, Lijun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Smooth Min-Max Monotonic Networks
Christian Igel
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Smooth Tchebycheff Scalarization for Multi-Objective Optimization
Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Fei Liu, Zhenkun Wang, Qingfu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Smoothing Proximal Gradient Methods for Nonsmooth Sparsity Constrained Optimization: Optimality Conditions and Global Convergence
Ganzhao Yuan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Smoothness Adaptive Hypothesis Transfer Learning
Haotian Lin, Matthew Reimherr
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sobolev Space Regularised Pre Density Models
Mark Kozdoba, Binyamin Perets, Shie Mannor
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Socialized Learning: Making Each Other Better Through Multi-Agent Collaboration
Xinjie Yao, Yu Wang, Pengfei Zhu, Wanyu Lin, Jialu Li, Weihao Li, Qinghua Hu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Soft Prompt Recovers Compressed LLMs, Transferably
Zhaozhuo Xu, Zirui Liu, Beidi Chen, Shaochen Zhong, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Solving Hierarchical Information-Sharing Dec-POMDPs: An Extensive-Form Game Approach
Johan Peralez, Aurélien Delage, Olivier Buffet, Jilles Steeve Dibangoye
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Solving Poisson Equations using Neural Walk-on-Spheres
Hong Chul Nam, Julius Berner, Anima Anandkumar
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SparQ Attention: Bandwidth-Efficient LLM Inference
Luka Ribar, Ivan Chelombiev, Luke Hudlass-Galley, Charlie Blake, Carlo Luschi, Douglas Orr
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once
Zhangheng Li, Shiwei Liu, Tianlong Chen, Ajay Kumar Jaiswal, Zhenyu Zhang, Dilin Wang, Raghuraman Krishnamoorthi, Shiyu Chang, Zhangyang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sparse Dimensionality Reduction Revisited
Mikael Møller Høgsgaard, Lior Kamma, Kasper Green Larsen, Jelani Nelson, Chris Schwiegelshohn
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference
Jian Xu, Delu Zeng, John Paisley
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sparse Model Inversion: Efficient Inversion of Vision Transformers for Data-Free Applications
Zixuan Hu, Yongxian Wei, Li Shen, Zhenyi Wang, Lei Li, Chun Yuan, Dacheng Tao
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sparse and Structured Hopfield Networks
Saul José Rodrigues Dos Santos, Vlad Niculae, Daniel C Mcnamee, Andre Martins
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sparse is Enough in Fine-tuning Pre-trained Large Language Models
Weixi Song, Zuchao Li, Lefei Zhang, Hai Zhao, Bo Du
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency
Vithursan Thangarasa, Shreyas Saxena, Abhay Gupta, Sean Lie
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sparse-to-dense Multimodal Image Registration via Multi-Task Learning
Kaining Zhang, Jiayi Ma
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SparseTSF: Modeling Long-term Time Series Forecasting with *1k* Parameters
Shengsheng Lin, Weiwei Lin, Wentai Wu, Haojun Chen, Junjie Yang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sparser, Better, Deeper, Stronger: Improving Static Sparse Training with Exact Orthogonal Initialization
Aleksandra Nowak, Łukasz Gniecki, Filip Szatkowski, Jacek Tabor
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Sparsest Models Elude Pruning: An Exposé of Pruning’s Current Capabilities
Stephen Zhang, Vardan Papyan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models
Pierre Mergny, Justin Ko, Florent Krzakala
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
Nikita Doikov, Sebastian U Stich, Martin Jaggi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Speech Self-Supervised Learning Using Diffusion Model Synthetic Data
Heting Gao, Kaizhi Qian, Junrui Ni, Chuang Gan, Mark A. Hasegawa-Johnson, Shiyu Chang, Yang Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Spider: A Unified Framework for Context-dependent Concept Segmentation
Xiaoqi Zhao, Youwei Pang, Wei Ji, Baicheng Sheng, Jiaming Zuo, Lihe Zhang, Huchuan Lu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Spike Distance Function as a Learning Objective for Spike Prediction
Kevin Doran, Marvin Seifert, Carola A. M. Yovanovich, Tom Baden
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms
Xingrun Xing, Zheng Zhang, Ziyi Ni, Shitao Xiao, Yiming Ju, Siqi Fan, Yequan Wang, Jiajun Zhang, Guoqi Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN
Kang You, Zekai Xu, Chen Nie, Zhijie Deng, Qinghai Guo, Xiang Wang, Zhezhi He
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting
Anthony Chen, Huanrui Yang, Yulu Gan, Denis A Gudovskiy, Zhen Dong, Haofan Wang, Tomoyuki Okuno, Yohei Nakata, Kurt Keutzer, Shanghang Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Split-and-Denoise: Protect large language model inference with local differential privacy
Peihua Mai, Ran Yan, Zhe Huang, Youjia Yang, Yan Pang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text
Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
SqueezeLLM: Dense-and-Sparse Quantization
Sehoon Kim, Coleman Richard Charles Hooper, Amir Gholami, Zhen Dong, Xiuyu Li, Sheng Shen, Michael W. Mahoney, Kurt Keutzer
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stability Evaluation through Distributional Perturbation Analysis
Jose Blanchet, Peng Cui, Jiajin Li, Jiashuo Liu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to $K$-Level Stochastic Optimizations
Xiaokang Pan, Xingyu Li, Jin Liu, Tao Sun, Kai Sun, Lixing Chen, Zhe Qu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms
Ming Yang, Xiyuan Wei, Tianbao Yang, Yiming Ying
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stability and Multigroup Fairness in Ranking with Uncertain Predictions
Siddartha Devic, Aleksandra Korolova, David Kempe, Vatsal Sharan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stability-Informed Initialization of Neural Ordinary Differential Equations
Theodor Westny, Arman Mohammadi, Daniel Jung, Erik Frisk
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process
Xiangxin Zhou, Liang Wang, Yichi Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stable Differentiable Causal Discovery
Achille Nazaret, Justin Hong, Elham Azizi, David Blei
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
StableMask: Refining Causal Masking in Decoder-only Transformer
Qingyu Yin, Xuzheng He, Xiang Zhuang, Yu Zhao, Jianhua Yao, Xiaoyu Shen, Qiang Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization
Shida Wang, Qianxiao Li
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
StackSight: Unveiling WebAssembly through Large Language Models and Neurosymbolic Chain-of-Thought Decompilation
Weike Fang, Zhejian Zhou, Junzhou He, Weihang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stacking Deep Set Networks and Pooling by Quantiles
Zhuojun Chen, Xinghua Zhu, Dongzhe Su, Justin C. I. Chuang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Standardized Interpretable Fairness Measures for Continuous Risk Scores
Ann-Kristin Becker, Oana Dumitrasc, Klaus Broelemann
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
State-Constrained Zero-Sum Differential Games with One-Sided Information
Mukesh Ghimire, Lei Zhang, Zhe Xu, Yi Ren
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
State-Free Inference of State-Space Models: The *Transfer Function* Approach
Rom Parnichkun, Stefano Massaroli, Alessandro Moro, Jimmy T.H. Smith, Ramin Hasani, Mathias Lechner, Qi An, Christopher Re, Hajime Asama, Stefano Ermon, Taiji Suzuki, Michael Poli, Atsushi Yamashita
Machine Learning
日本大学: 中央大学 / 東京大学
2024 · ICML
Stationarity without mean reversion in improper Gaussian processes
Luca Ambrogioni
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stationary Latent Weight Inference for Unreliable Observations from Online Test-Time Adaptation
Jae-Hong Lee, Joon-Hyuk Chang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Statistical Inference Under Constrained Selection Bias
Santiago Cortes-Gomez, Mateo Dulce Rubio, Carlos Miguel Patiño, Bryan Wilder
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Statistical Properties of Robust Satisficing
Zhiyi Li, Yunbei Xu, Ruohan Zhan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Statistical Test for Attention Maps in Vision Transformers
Tomohiro Shiraishi, Daiki Miwa [東京科学大学] [名古屋工業大学], Teruyuki Katsuoka, Vo Nguyen Le Duy, Kouichi Taji, Ichiro Takeuchi
Machine Learning
日本大学: 東京科学大学 / 名古屋工業大学 / 名古屋大学
2024 · ICML
Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution
Elen Vardanyan, Sona Hunanyan, Tigran Galstyan, Arshak Minasyan, Arnak S. Dalalyan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stay on Topic with Classifier-Free Guidance
Guillaume Sanchez, Alexander Spangher, Honglu Fan, Elad Levi, Stella Biderman
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stealing part of a production language model
Nicholas Carlini, Daniel Paleka, Krishnamurthy Dj Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stealthy Imitation: Reward-guided Environment-free Policy Stealing
Zhixiong Zhuang, Maria-Irina Nicolae, Mario Fritz
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stereo Risk: A Continuous Modeling Approach to Stereo Matching
Ce Liu, Suryansh Kumar, Shuhang Gu, Radu Timofte, Yao Yao, Luc Van Gool
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stereographic Spherical Sliced Wasserstein Distances
Huy Tran, Yikun Bai, Abihith Kothapalli, Ashkan Shahbazi, Xinran Liu, Rocio P Diaz Martin, Soheil Kolouri
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stochastic Bandits with ReLU Neural Networks
Kan Xu, Hamsa Bastani, Surbhi Goel, Osbert Bastani
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis
Juyeon Ko, Inho Kong, Dogyun Park, Hyunwoo J. Kim
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features
Rodrigo Veiga, Anastasia Remizova, Nicolas Macris
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stochastic Interpolants with Data-Dependent Couplings
Michael Samuel Albergo, Mark Goldstein, Nicholas Matthew Boffi, Rajesh Ranganath, Eric Vanden-Eijnden
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stochastic Localization via Iterative Posterior Sampling
Louis Grenioux, Maxence Noble, Marylou Gabrié, Alain Oliviero Durmus
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stochastic Optimization with Arbitrary Recurrent Data Sampling
William Powell, Hanbaek Lyu
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stochastic Q-learning for Large Discrete Action Spaces
Fares Fourati, Vaneet Aggarwal, Mohamed-Slim Alouini
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stochastic Quantum Sampling for Non-Logconcave Distributions and Estimating Partition Functions
Guneykan Ozgul, Xiantao Li, Mehrdad Mahdavi, Chunhao Wang
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stochastic Weakly Convex Optimization beyond Lipschitz Continuity
Wenzhi Gao, Qi Deng
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stochastic positional embeddings improve masked image modeling
Amir Bar, Florian Bordes, Assaf Shocher, Mido Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann Lecun
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taiga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Sergey Levine, Pablo Samuel Castro, Aleksandra Faust, Aviral Kumar, Rishabh Agarwal
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
StrWAEs to Invariant Representations
Hyunjong Lee, Yedarm Seong, Sungdong Lee, Joong-Ho Won
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Straight-Through Meets Sparse Recovery: the Support Exploration Algorithm
Mimoun Mohamed, Francois Malgouyres, Valentin Emiya, Caroline Chaux
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
StrokeNUWA—Tokenizing Strokes for Vector Graphic Synthesis
Zecheng Tang, Chenfei Wu, Zekai Zhang, Minheng Ni, Shengming Yin, Yu Liu, Zhengyuan Yang, Lijuan Wang, Zicheng Liu, Juntao Li, Nan Duan
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Structure Your Data: Towards Semantic Graph Counterfactuals
Angeliki Dimitriou, Maria Lymperaiou, Georgios Filandrianos, Konstantinos Thomas, Giorgos Stamou
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks
Duy Minh Ho Nguyen, Nina Lukashina, Tai Nguyen, An Thai Le, Trungtin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Structure-based drug design by denoising voxel grids
Pedro O. Pinheiro, Arian Rokkum Jamasb, Omar Mahmood, Vishnu Sresht, Saeed Saremi
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Structured Chemistry Reasoning with Large Language Models
Siru Ouyang, Zhuosheng Zhang, Bing Yan, Xuan Liu, Yejin Choi, Jiawei Han, Lianhui Qin
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC
Wu Lin, Felix Dangel, Runa Eschenhagen, Kirill Neklyudov, Agustinus Kristiadi, Richard E. Turner, Alireza Makhzani
Machine Learning
日本大学: 関与なし（対象大学）
2024 · ICML
Studying K-FAC Heuristics by Viewing Adam through a Second-Order Lens
Ross M Clarke, José Miguel Hernández-Lobato
Machine Learning
日本大学: 関与なし（対象大学）