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 | TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting. | Peiyuan Liu, Beiliang Wu, Yifan Hu, Naiqi Li, Tao Dai, Jigang Bao, Shu-Tao Xia |
| 2025 | Censor Dependent Variational Inference. | Chuanhui Liu, Xiao Wang |
| 2025 | Mutual Learning for SAM Adaptation: A Dual Collaborative Network Framework for Source-Free Domain Transfer. | Yabo Liu, Waikeung Wong, Chengliang Liu, Xiaoling Luo, Yong Xu, Jinghua Wang |
| 2025 | Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization. | Duo Liu, Zhiquan Tan, Linglan Zhao, Zhongqiang Zhang, Xiangzhong Fang, Weiran Huang |
| 2025 | Fast Estimation of Partial Dependence Functions using Trees. | Jinyang Liu, Tessa Steensgaard, Marvin N. Wright, Niklas Pfister, Munir Hiabu |
| 2025 | Segment Anyword: Mask Prompt Inversion for Open-Set Grounded Segmentation. | Zhihua Liu, Amrutha Saseendran, Lei Tong, Xilin He, Fariba Yousefi, Nikolay Burlutskiy, Dino Oglic, Tom Diethe, Philip Alexander Teare, Huiyu Zhou, Chen Jin |
| 2025 | Efficient ANN-SNN Conversion with Error Compensation Learning. | Chang Liu, Jiangrong Shen, Xuming Ran, Mingkun Xu, Qi Xu, Yi Xu, Gang Pan |
| 2025 | Self-Supervised Learning of Intertwined Content and Positional Features for Object Detection. | Kang-Jun Liu, Masanori Suganuma, Takayuki Okatani |
| 2025 | ProofAug: Efficient Neural Theorem Proving via Fine-grained Proof Structure Analysis. | Haoxiong Liu, Jiacheng Sun, Zhenguo Li, Andrew C. Yao |
| 2025 | Proxsparse: Regularized Learning of Semi-Structured Sparsity masks for Pretrained LLMS. | Hongyi Liu, Rajarshi Saha, Zhen Jia, Youngsuk Park, Jiaji Huang, Shoham Sabach, Yu-Xiang Wang, George Karypis |
| 2025 | Accurate Identification of Communication Between Multiple Interacting Neural Populations. | Belle Liu, Jacob Sacks, Matthew D. Golub |
| 2025 | AutoStep: Locally adaptive involutive MCMC. | Tiange Liu, Nikola Surjanovic, Miguel Biron-Lattes, Alexandre Bouchard-Ct, Trevor Campbell |
| 2025 | Position: Truly Self-Improving Agents Require Intrinsic Metacognitive Learning. | Tennison Liu, Mihaela van der Schaar |
| 2025 | Slimming the Fat-Tail: Morphing-Flow for Adaptive Time Series Modeling. | Tianyu Liu, Kai Sun, Fuchun Sun, Yu Luo, Yuanlong Zhang |
| 2025 | Generative Human Trajectory Recovery via Embedding-Space Conditional Diffusion. | Kaijun Liu, Sijie Ruan, Liang Zhang, Cheng Long, Shuliang Wang, Liang Yu |
| 2025 | Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents. | Junyan Liu, Lillian J. Ratliff |
| 2025 | Sundial: A Family of Highly Capable Time Series Foundation Models. | Yong Liu, Guo Qin, Zhiyuan Shi, Zhi Chen, Caiyin Yang, Xiangdong Huang, Jianmin Wang, Mingsheng Long |
| 2025 | Deliberation in Latent Space via Differentiable Cache Augmentation. | Luyang Liu, Jonas Pfeiffer, Jiaxing Wu, Jun Xie, Arthur Szlam |
| 2025 | LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning. | Zihang Liu, Tianyu Pang, Oleg Balabanov, Chaoqun Yang, Tianjin Huang, Lu Yin, Yaoqing Yang, Shiwei Liu |
| 2025 | Permutation-Free High-Order Interaction Tests. | Zhaolu Liu, Robert L. Peach, Mauricio Barahona |
| 2025 | Reward Modeling with Ordinal Feedback: Wisdom of the Crowd. | Shang Liu, Yu Pan, Guanting Chen, Xiaocheng Li |
| 2025 | The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning. | Jiashun Liu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan |
| 2025 | Efficient Robotic Policy Learning via Latent Space Backward Planning. | Dongxiu Liu, Haoyi Niu, Zhihao Wang, Jinliang Zheng, Yinan Zheng, Zhonghong Ou, Jianming Hu, Jianxiong Li, Xianyuan Zhan |
| 2025 | Understanding the Unfairness in Network Quantization. | Bing Liu, Wenjun Miao, Boyu Zhang, Qiankun Zhang, Bin Yuan, Jing Wang, Shenghao Liu, Xianjun Deng |
| 2025 | Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals. | Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin Jamieson, Lillian J. Ratliff |
1,576–1,600 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)