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 | LADA: Scalable Label-Specific CLIP Adapter for Continual Learning. | Mao-Lin Luo, Zi-Hao Zhou, Tong Wei, Min-Ling Zhang |
| 2025 | Hi-Patch: Hierarchical Patch GNN for Irregular Multivariate Time Series. | Yicheng Luo, Bowen Zhang, Zhen Liu, Qianli Ma |
| 2025 | Causal Attribution Analysis for Continuous Outcomes. | Shanshan Luo, Yixuan Yu, Chunchen Liu, Feng Xie, Zhi Geng |
| 2025 | Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL. | Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang |
| 2025 | Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries. | Huakun Luo, Haixu Wu, Hang Zhou, Lanxiang Xing, Yichen Di, Jianmin Wang, Mingsheng Long |
| 2025 | Locality Preserving Markovian Transition for Instance Retrieval. | Jifei Luo, Wenzheng Wu, Hantao Yao, Lu Yu, Changsheng Xu |
| 2025 | Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity. | Erpai Luo, Xinran Wei, Lin Huang, Yunyang Li, Han Yang, Zaishuo Xia, Zun Wang, Chang Liu, Bin Shao, Jia Zhang |
| 2025 | Beyond One-Hot Labels: Semantic Mixing for Model Calibration. | Haoyang Luo, Linwei Tao, Minjing Dong, Chang Xu |
| 2025 | Sparsing Law: Towards Large Language Models with Greater Activation Sparsity. | Yuqi Luo, Chenyang Song, Xu Han, Yingfa Chen, Chaojun Xiao, Xiaojun Meng, Liqun Deng, Jiansheng Wei, Zhiyuan Liu, Maosong Sun |
| 2025 | Fast and Low-Cost Genomic Foundation Models via Outlier Removal. | Haozheng Luo, Chenghao Qiu, Maojiang Su, Zhihan Zhou, Zoe Mehta, Guo Ye, Jerry Yao-Chieh Hu, Han Liu |
| 2025 | Occult: Optimizing Collaborative Communications across Experts for Accelerated Parallel MoE Training and Inference. | Shuqing Luo, Pingzhi Li, Jie Peng, Yang Zhao, Yu Cao, Yu Cheng, Tianlong Chen |
| 2025 | Quantum Algorithms for Finite-horizon Markov Decision Processes. | Bin Luo, Yuwen Huang, Jonathan Allcock, Xiaojun Lin, Shengyu Zhang, John C. S. Lui |
| 2025 | Vision-Language Models Create Cross-Modal Task Representations. | Grace Luo, Trevor Darrell, Amir Bar |
| 2025 | Probing Visual Language Priors in VLMs. | Tiange Luo, Ang Cao, Gunhee Lee, Justin Johnson, Honglak Lee |
| 2025 | Stacey: Promoting Stochastic Steepest Descent via Accelerated ℓp-Smooth Nonconvex Optimization. | Xinyu Luo, Site Bai, Bolian Li, Petros Drineas, Ruqi Zhang, Brian Bullins |
| 2025 | One-dimensional Path Convolution. | Xuanshu Luo, Martin Werner |
| 2025 | Can Classic GNNs Be Strong Baselines for Graph-level Tasks? Simple Architectures Meet Excellence. | Yuankai Luo, Lei Shi, Xiao-Ming Wu |
| 2025 | Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation. | Michal Lukasik, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Felix X. Yu, Sashank J. Reddi, Gang Fu, MohammadHossein Bateni, Sanjiv Kumar |
| 2025 | Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling. | Shuqi Lu, Xiaohong Ji, Bohang Zhang, Lin Yao, Siyuan Liu, Zhifeng Gao, Linfeng Zhang, Guolin Ke |
| 2025 | Towards Practical Defect-Focused Automated Code Review. | Junyi Lu, Lili Jiang, Xiaojia Li, Jianbing Fang, Fengjun Zhang, Li Yang, Chun Zuo |
| 2025 | WAVE: Weighted Autoregressive Varying Gate for Time Series Forecasting. | Jiecheng Lu, Xu Han, Yan Sun, Shihao Yang |
| 2025 | Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient. | Jan Ludziejewski, Maciej Piro, Jakub Krajewski, Maciej Stefaniak, Michal Krutul, Jan Malasnicki, Marek Cygan, Piotr Sankowski, Kamil Adamczewski, Piotr Milos, Sebastian Jaszczur |
| 2025 | Aligning Protein Conformation Ensemble Generation with Physical Feedback. | Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Aurlie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang |
| 2025 | Learning with Expected Signatures: Theory and Applications. | Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart |
| 2025 | Positional Attention: Expressivity and Learnability of Algorithmic Computation. | Artur Back de Luca, George Giapitzakis, Shenghao Yang, Petar Velickovic, Kimon Fountoulakis |
1,501–1,525 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)