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Machine Learning

2025 · 3,330 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。

2025 · ICML
Clustering Items through Bandit Feedback: Finding the Right Feature out of Many
Maximilian Graf, Thuot Victor, Nicolas Verzelen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Clustering Properties of Self-Supervised Learning
Xi Weng, Jianing An, Xudong Ma, Binhang Qi, Jie Luo, Xi Yang, Jin Song Dong, Lei Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Clustering via Self-Supervised Diffusion
Roy Uziel, Irit Chelly, Oren Freifeld, Ari Pakman
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CoCoA-Mix: Confusion-and-Confidence-Aware Mixture Model for Context Optimization
Dasol Hong, Wooju Lee, Hyun Myung
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CoDy: Counterfactual Explainers for Dynamic Graphs
Zhan Qu, Daniel Gomm, Michael Färber
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CoMemo: LVLMs Need Image Context with Image Memory
Shi Liu, Weijie Su, Xizhou Zhu, Wenhai Wang, Jifeng Dai
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CoPINN: Cognitive Physics-Informed Neural Networks
Siyuan Duan, Wenyuan Wu, Peng Hu, Zhenwen Ren, Dezhong Peng, Yuan Sun
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CoSER: Coordinating LLM-Based Persona Simulation of Established Roles
Xintao Wang, Heng Wang, Yifei Zhang, Xinfeng Yuan, Rui Xu, Jen-Tse Huang, Siyu Yuan, Haoran Guo, Jiangjie Chen, Shuchang Zhou, Wei Wang, Yanghua Xiao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CoastalBench: A Decade-Long High-Resolution Dataset to Emulate Complex Coastal Processes
Zelin Xu, Yupu Zhang, Tingsong Xiao, Maitane Olabarrieta Lizaso, Jose M. Gonzalez-Ondina, Zibo Liu, Shigang Chen, Zhe Jiang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Code-Generated Graph Representations Using Multiple LLM Agents for Material Properties Prediction
Jiao Huang, Qianli Xing, Jinglong Ji, Bo Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CodeIO: Condensing Reasoning Patterns via Code Input-Output Prediction
Junlong Li, Daya Guo, Dejian Yang, Runxin Xu, Yu Wu, Junxian He
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CodeSteer: Symbolic-Augmented Language Models via Code/Text Guidance
Yongchao Chen, Yilun Hao, Yueying Liu, Yang Zhang, Chuchu Fan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CodeSync: Synchronizing Large Language Models with Dynamic Code Evolution at Scale
Chenlong Wang, Zhaoyang Chu, Zhengxiang Cheng, Xuyi Yang, Kaiyue Qiu, Yao Wan, Zhou Zhao, Xuanhua Shi, Hai Jin, Dongping Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CogMath: Assessing LLMs’ Authentic Mathematical Ability from a Human Cognitive Perspective
Jiayu Liu, Zhenya Huang, Wei Dai, Cheng Cheng, Jinze Wu, Jing Sha, Song Li, Qi Liu, Shijin Wang, Enhong Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CogReact: A Reinforced Framework to Model Human Cognitive Reaction Modulated by Dynamic Intervention
Songlin Xu, Xinyu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CollabLLM: From Passive Responders to Active Collaborators
Shirley Wu, Michel Galley, Baolin Peng, Hao Cheng, Gavin Li, Yao Dou, Weixin Cai, James Zou, Jure Leskovec, Jianfeng Gao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution
Alex Clinton, Yiding Chen, Jerry Zhu, Kirthevasan Kandasamy
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World
Joshua Kazdan, Rylan Schaeffer, Apratim Dey, Matthias Gerstgrasser, Rafael Rafailov, David L. Donoho, Sanmi Koyejo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Collapse-Proof Non-Contrastive Self-Supervised Learning
Emanuele Sansone, Tim Lebailly, Tinne Tuytelaars
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule Generation
Thibaud Southiratn, Bonil Koo, Yijingxiu Lu, Sun Kim
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Combinatorial Reinforcement Learning with Preference Feedback
Joongkyu Lee, Min-Hwan Oh
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation
Zhan Zhuang, Xiequn Wang, Wei Li, Yulong Zhang, Qiushi Huang, Shuhao Chen, Xuehao Wang, Yanbin Wei, Yuhe Nie, Kede Ma, Yu Zhang, Ying Wei
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
CommVQ: Commutative Vector Quantization for KV Cache Compression
Junyan Li, Yang Zhang, Muhammad Yusuf Hassan, Talha Chafekar, Tianle Cai, Zhile Ren, Pengsheng Guo, Foroozan Karimzadeh, Colorado Reed, Chong Wang, Chuang Gan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Communicating Activations Between Language Model Agents
Vignav Ramesh, Kenneth Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Commute Graph Neural Networks
Wei Zhuo, Han Yu, Guang Tan, Xiaoxiao Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compact Matrix Quantum Group Equivariant Neural Networks
Edward Pearce-Crump
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries
Xuening Feng, Zhaohui Jiang, Timo Kaufmann, Eyke Hüllermeier, Paul Weng, Yifei Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Comparing Few to Rank Many: Active Human Preference Learning Using Randomized Frank-Wolfe Method
Kiran Koshy Thekumparampil, Gaurush Hiranandani, Kousha Kalantari, Shoham Sabach, Branislav Kveton
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training
Max Milkert, David Hyde, Forrest John Laine
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Competing Bandits in Matching Markets via Super Stability
Soumya Basu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Competitively Consistent Clustering
Niv Buchbinder, Roie Levin, Yue Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Complete-Tree Space Favors Data-Efficient Link Prediction
Chi Gao, Lukai Li, Yancheng Zhou, Shangqi Guo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Complex Wavelet Mutual Information Loss: A Multi-Scale Loss Function for Semantic Segmentation
Renhao Lu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Componential Prompt-Knowledge Alignment for Domain Incremental Learning
Kunlun Xu, Xu Zou, Gang Hua, Jiahuan Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compositional Causal Reasoning Evaluation in Language Models
Jacqueline R. M. A. Maasch, Alihan Hüyük, Xinnuo Xu, Aditya V. Nori, Javier Gonzalez
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compositional Condition Question Answering in Tabular Understanding
Jun-Peng Jiang, Tao Zhou, De-Chuan Zhan, Han-Jia Ye
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compositional Flows for 3D Molecule and Synthesis Pathway Co-design
Tony Shen, Seonghwan Seo, Ross Irwin, Kieran Didi, Simon Olsson, Woo Youn Kim, Martin Ester
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compositional Generalization via Forced Rendering of Disentangled Latents
Qiyao Liang, Daoyuan Qian, Liu Ziyin, Ila R Fiete
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compositional Risk Minimization
Divyat Mahajan, Mohammad Pezeshki, Charles Arnal, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compositional Scene Understanding through Inverse Generative Modeling
Yanbo Wang, Justin Dauwels, Yilun Du
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan Greenewald, Mikhail Yurochkin, Justin Solomon
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compressed Image Generation with Denoising Diffusion Codebook Models
Guy Ohayon, Hila Manor, Tomer Michaeli, Michael Elad
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compressing tree ensembles through Level-wise Optimization and Pruning
Laurens Devos, Timo Martens, Deniz Can Oruc, Wannes Meert, Hendrik Blockeel, Jesse Davis
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data
David Heurtel-Depeiges, Anian Ruoss, Joel Veness, Tim Genewein
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders
Charles O’Neill, Alim Gumran, David Klindt
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Compute or Load KV Cache? Why Not Both?
Shuowei Jin, Xueshen Liu, Qingzhao Zhang, Zhuoqing Mao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows
Gabriele Visentin, Patrick Cheridito
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Computing Voting Rules with Improvement Feedback
Evi Micha, Vasilis Varsamis
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ConText: Driving In-context Learning for Text Removal and Segmentation
Fei Zhang, Pei Zhang, Baosong Yang, Fei Huang, Yanfeng Wang, Ya Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Concentration Distribution Learning from Label Distributions
Jiawei Tang, Yuheng Jia
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Concept Reachability in Diffusion Models: Beyond Dataset Constraints
Marta Aparicio Rodriguez, Xenia Miscouridou, Anastasia Borovykh
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Concept-Based Unsupervised Domain Adaptation
Xinyue Xu, Yueying Hu, Hui Tang, Yi Qin, Lu Mi, Hao Wang, Xiaomeng Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Concept-Centric Token Interpretation for Vector-Quantized Generative Models
Tianze Yang, Yucheng Shi, Mengnan Du, Xuansheng Wu, Qiaoyu Tan, Jin Sun, Ninghao Liu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
Alec Helbling, Tuna Han Salih Meral, Benjamin Hoover, Pinar Yanardag, Duen Horng Chau
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Concurrent Reinforcement Learning with Aggregated States via Randomized Least Squares Value Iteration
Yan Chen, Qinxun Bai, Yiteng Zhang, Maria Dimakopoulou, Shi Dong, Qi Sun, Zhengyuan Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting
J Rishi, Gvs Mothish, Deepak Subramani
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Conditioning Diffusions Using Malliavin Calculus
Jakiw Pidstrigach, Elizabeth Louise Baker, Carles Domingo-Enrich, George Deligiannidis, Nikolas Nüsken
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference Optimization
Hee Suk Yoon, Eunseop Yoon, Mark A. Hasegawa-Johnson, Sungwoong Kim, Chang D. Yoo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Confidence Difference Reflects Various Supervised Signals in Confidence-Difference Classification
Yuanchao Dai, Ximing Li, Changchun Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention
Stephan Rabanser, Ali Shahin Shamsabadi, Olive Franzese, Xiao Wang, Adrian Weller, Nicolas Papernot
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Conformal Anomaly Detection in Event Sequences
Shuai Zhang, Chuan Zhou, Yang Liu, Peng Zhang, Xixun Lin, Shirui Pan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Conformal Prediction as Bayesian Quadrature
Jake C. Snell, Thomas L. Griffiths
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach
Qian Peng, Yajie Bao, Haojie Ren, Zhaojun Wang, Changliang Zou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Conformal Tail Risk Control for Large Language Model Alignment
Catherine Chen, Jingyan Shen, Zhun Deng, Lihua Lei
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Conformity Score Averaging for Classification
Rui Luo, Zhixin Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Confounder-Free Continual Learning via Recursive Feature Normalization
Yash Shah, Camila Gonzalez, Mohammad H. Abbasi, Qingyu Zhao, Kilian M. Pohl, Ehsan Adeli
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret
Bingshan Hu, Zhiming Huang, Tianyue H. Zhang, Mathias Lécuyer, Nidhi Hegde
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Consensus Based Stochastic Optimal Control
Liyao Lyu, Jingrun Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Consensus Is All You Get: The Role of Attention in Transformers
Álvaro Rodrı́guez Abella, João Pedro Silvestre, Paulo Tabuada
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Conservative Offline Goal-Conditioned Implicit V-Learning
Kaiqiang Ke, Qian Lin, Zongkai Liu, Shenghong He, Chao Yu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability
Michael Crawshaw, Blake Woodworth, Mingrui Liu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Constrain Alignment with Sparse Autoencoders
Qingyu Yin, Chak Tou Leong, Hongbo Zhang, Minjun Zhu, Hanqi Yan, Qiang Zhang, Yulan He, Wenjie Li, Jun Wang, Yue Zhang, Linyi Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Constrained Belief Updates Explain Geometric Structures in Transformer Representations
Mateusz Piotrowski, Paul M. Riechers, Daniel Filan, Adam Shai
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Constrained Exploitability Descent: An Offline Reinforcement Learning Method for Finding Mixed-Strategy Nash Equilibrium
Runyu Lu, Yuanheng Zhu, Dongbin Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Constrained Online Convex Optimization with Polyak Feasibility Steps
Spencer Hutchinson, Mahnoosh Alizadeh
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Constrained Pareto Set Identification with Bandit Feedback
Cyrille Kone, Emilie Kaufmann, Laura Richert
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Context Matters: Query-aware Dynamic Long Sequence Modeling of Gigapixel Images
Zhengrui Guo, Qichen Sun, Jiabo Ma, Lishuang Feng, Jinzhuo Wang, Hao Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Context is Key: A Benchmark for Forecasting with Essential Textual Information
Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf Theorem
In Huh, Changwook Jeong, Muhammad Alam
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contextual Bandits for Unbounded Context Distributions
Puning Zhao, Rongfei Fan, Shaowei Wang, Li Shen, Qixin Zhang, Zong Ke, Tianhang Zheng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contextual Linear Bandits with Delay as Payoff
Mengxiao Zhang, Yingfei Wang, Haipeng Luo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contextual Online Decision Making with Infinite-Dimensional Functional Regression
Haichen Hu, Rui Ai, Stephen Bates, David Simchi-Levi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contextual Optimization Under Model Misspecification: A Tractable and Generalizable Approach
Omar Bennouna, Jiawei Zhang, Saurabh Amin, Asuman E. Ozdaglar
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contextures: Representations from Contexts
Runtian Zhai, Kai Yang, Burak Varıcı, Che-Ping Tsai, J Zico Kolter, Pradeep Kumar Ravikumar
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian Perspective
Hao Dai, Jagmohan Chauhan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Continual Reinforcement Learning by Planning with Online World Models
Zichen Liu, Guoji Fu, Chao Du, Wee Sun Lee, Min Lin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Continuous Bayesian Model Selection for Multivariate Causal Discovery
Anish Dhir, Ruby Sedgwick, Avinash Kori, Ben Glocker, Mark Van Der Wilk
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Continuous Semi-Implicit Models
Longlin Yu, Jiajun Zha, Tong Yang, Tianyu Xie, Xiangyu Zhang, S.-H. Chan, Cheng Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Continuous Visual Autoregressive Generation via Score Maximization
Chenze Shao, Fandong Meng, Jie Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Continuous-Time Analysis of Heavy Ball Momentum in Min-Max Games
Yi Feng, Kaito Fujii, Stratis Skoulakis, Xiao Wang, Volkan Cevher
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Continuously Updating Digital Twins using Large Language Models
Harry Amad, Nicolás Astorga, Mihaela Van Der Schaar
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contour Integration Underlies Human-Like Vision
Ben Lonnqvist, Elsa Scialom, Abdulkadir Gokce, Zehra Merchant, Michael Herzog, Martin Schrimpf
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contract Design Under Approximate Best Responses
Francesco Bacchiocchi, Jiarui Gan, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contradiction Retrieval via Contrastive Learning with Sparsity
Haike Xu, Zongyu Lin, Kai-Wei Chang, Yizhou Sun, Piotr Indyk
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contrastive Learning with Simplicial Convolutional Networks for Short-Text Classification
Huang Liang, Benedict Lee, Daniel Hui Loong Ng, Kelin Xia
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contrastive Localized Language-Image Pre-Training
Hong-You Chen, Zhengfeng Lai, Haotian Zhang, Xinze Wang, Marcin Eichner, Keen You, Meng Cao, Bowen Zhang, Yinfei Yang, Zhe Gan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion
Tianyuan Zou, Yang Liu, Peng Li, Yufei Xiong, Jianqing Zhang, Jingjing Liu, Xiaozhou Ye, Ye Ouyang, Ya-Qin Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Contrastive Visual Data Augmentation
Yu Zhou, Bingxuan Li, Tang Mohan, Xiaomeng Jin, Te-Lin Wu, Kuan-Hao Huang, Heng Ji, Kai-Wei Chang, Nanyun Peng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Control and Realism: Best of Both Worlds in Layout-to-Image without Training
Bonan Li, Yinhan Hu, Songhua Liu, Xinchao Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Controllable Data Generation with Hierarchical Neural Representations
Sheyang Tang, Xiaoyu Xu, Jiayan Qiu, Zhou Wang
Machine Learning
日本大学: 関与なし（対象大学）