International Conference on Machine Learning
ICML
A*
CORE rank
CORE rank (raw)
A*
Acceptance rate
27.5% (2024)
Fields of research
Machine Learning
Papers indexed
17,065
1988–2025
Papers per year
19883,341 peak2025
Most published authors
ICML papers
17,065 records sourced from DBLP. Search titles, filter by year, sort by recency.
| Year | Title | Authors |
|---|---|---|
| 2025 | Scaling Sparse Feature Circuits For Studying In-Context Learning. | Dmitrii Kharlapenko, Stepan Shabalin, Arthur Conmy, Neel Nanda |
| 2025 | ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts. | Samar Khanna, Medhanie Irgau, David B. Lobell, Stefano Ermon |
| 2025 | FlexiClip: Locality-Preserving Free-Form Character Animation. | Anant Khandelwal |
| 2025 | SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity. | Samir Khaki, Xiuyu Li, Junxian Guo, Ligeng Zhu, Konstantinos N. Plataniotis, Amir Yazdanbakhsh, Kurt Keutzer, Song Han, Zhijian Liu |
| 2025 | Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors. | Jingyang Ke, Feiyang Wu, Jiyi Wang, Jeffrey Markowitz, Anqi Wu |
| 2025 | ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy. | Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik, Konstantin Donhauser, Jason S. Hartford, Saber Saberian, Nil Sahin, Ihab Bendidi, Safiye Celik, Juan Sebastin Rodrguez Vera, Marta M. Fay, Imran S. Haque, Oren Kraus |
| 2025 | When and How Does CLIP Enable Domain and Compositional Generalization? | Elias Kempf, Simon Schrodi, Max Argus, Thomas Brox |
| 2025 | Scalable Meta-Learning via Mixed-Mode Differentiation. | Iurii Kemaev, Dan A. Calian, Luisa M. Zintgraf, Gregory Farquhar, Hado van Hasselt |
| 2025 | WyckoffDiff - A Generative Diffusion Model for Crystal Symmetry. | Filip Ekstrm Kelvinius, Oskar B. Andersson, Abhijith S. Parackal, Dong Qian, Rickard Armiento, Fredrik Lindsten |
| 2025 | Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlo. | Filip Ekstrm Kelvinius, Zheng Zhao, Fredrik Lindsten |
| 2025 | Bayesian Inference for Correlated Human Experts and Classifiers. | Markelle Kelly, Alex James Boyd, Samuel Showalter, Mark Steyvers, Padhraic Smyth |
| 2025 | Conservative Offline Goal-Conditioned Implicit V-Learning. | Kaiqiang Ke, Qian Lin, Zongkai Liu, Shenghong He, Chao Yu |
| 2025 | Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models. | Armin Kekic, Sergio Hernan Garrido Mejia, Bernhard Schlkopf |
| 2025 | Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion. | Anle Ke, Xu Zhang, Tong Chen, Ming Lu, Chao Zhou, Jiawen Gu, Zhan Ma |
| 2025 | VinePPO: Refining Credit Assignment in RL Training of LLMs. | Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, Alessandro Sordoni, Siva Reddy, Aaron C. Courville, Nicolas Le Roux |
| 2025 | Model-Based Exploration in Monitored Markov Decision Processes. | Alireza Kazemipour, Matthew E. Taylor, Michael Bowling |
| 2025 | Wyckoff Transformer: Generation of Symmetric Crystals. | Nikita Kazeev, Wei Nong, Ignat Romanov, Ruiming Zhu, Andrey E. Ustyuzhanin, Shuya Yamazaki, Kedar Hippalgaonkar |
| 2025 | 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 |
| 2025 | Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds. | Aya Kayal, Sattar Vakili, Laura Toni, Da-shan Shiu, Alberto Bernacchia |
| 2025 | Mixture of Experts Provably Detect and Learn the Latent Cluster Structure in Gradient-Based Learning. | Ryotaro Kawata, Kohsei Matsutani, Yuri Kinoshita, Naoki Nishikawa, Taiji Suzuki |
| 2025 | Leveraging Offline Data in Linear Latent Contextual Bandits. | Chinmaya Kausik, Kevin Tan, Ambuj Tewari |
| 2025 | Curvature Enhanced Data Augmentation for Regression. | Ilya Kaufman, Omri Azencot |
| 2025 | Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics. | Tyler Kastner, Mark Rowland, Yunhao Tang, Murat A. Erdogdu, Amir-massoud Farahmand |
| 2025 | One Wave To Explain Them All: A Unifying Perspective On Feature Attribution. | Gabriel Kasmi, Amandine Brunetto, Thomas Fel, Jayneel Parekh |
| 2025 | SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability. | Adam Karvonen, Can Rager, Johnny Lin, Curt Tigges, Joseph Isaac Bloom, David Chanin, Yeu-Tong Lau, Eoin Farrell, Callum McDougall, Kola Ayonrinde, Demian Till, Matthew Wearden, Arthur Conmy, Samuel Marks, Neel Nanda |
1,926–1,950 of 17,065← PreviousNext →
Comparable venues
Other A*/A conferences filed under the same field of research.
- A*ICLRInternational Conference on Learning Representations
- AAISTATSInternational Conference on Artificial Intelligence and Statistics
- A*COLTConference on Learning Theory
- APPSNParallel Problem Solving from Nature
- AECML PKDDEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (PKDD and ECML combined from 2008)
- A*NeurIPSAdvances in Neural Information Processing Systems (was NIPS)