International Conference on Learning Representations
ICLR
A*
CORE rank
CORE rank (raw)
A*
Acceptance rate
31.7% (2024)
Fields of research
Machine Learning
Papers indexed
11,991
2017–2025
Papers per year
20173,704 peak2025
Most published authors
ICLR papers
11,991 records sourced from DBLP. Search titles, filter by year, sort by recency.
| Year | Title | Authors |
|---|---|---|
| 2025 | Two Sparse Matrices are Better than One: Sparsifying Neural Networks with Double Sparse Factorization. | Vladimr Boza, Vladimr Macko |
| 2025 | Action abstractions for amortized sampling. | Oussama Boussif, Lna Nhale Ezzine, Joseph D. Viviano, Michal Koziarski, Moksh Jain, Nikolay Malkin, Emmanuel Bengio, Rim Assouel, Yoshua Bengio |
| 2025 | Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models. | Tho Bourdais, Houman Owhadi |
| 2025 | Tailoring Mixup to Data for Calibration. | Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alch-Buc |
| 2025 | Learning Geometric Reasoning Networks For Robot Task And Motion Planning. | Smail Ait Bouhsain, Rachid Alami, Thierry Simon |
| 2025 | Open-YOLO 3D: Towards Fast and Accurate Open-Vocabulary 3D Instance Segmentation. | Mohamed El Amine Boudjoghra, Angela Dai, Jean Lahoud, Hisham Cholakkal, Rao Muhammad Anwer, Salman H. Khan, Fahad Shahbaz Khan |
| 2025 | Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods. | Lise Le Boudec, Emmanuel de Bzenac, Louis Serrano, Ramon Daniel Regueiro-Espino, Yuan Yin, Patrick Gallinari |
| 2025 | Data Taggants: Dataset Ownership Verification Via Harmless Targeted Data Poisoning. | Wassim Bouaziz, Nicolas Usunier, El-Mahdi El-Mhamdi |
| 2025 | Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research. | Michal Bortkiewicz, Wladyslaw Palucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Lukasz Kucinski, Benjamin Eysenbach |
| 2025 | Training Robust Ensembles Requires Rethinking Lipschitz Continuity. | Ali Ebrahimpour Boroojeny, Hari Sundaram, Varun Chandrasekaran |
| 2025 | How Feature Learning Can Improve Neural Scaling Laws. | Blake Bordelon, Alexander B. Atanasov, Cengiz Pehlevan |
| 2025 | Neural Spacetimes for DAG Representation Learning. | Haitz Sez de Ocriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein |
| 2025 | AIMS.au: A Dataset for the Analysis of Modern Slavery Countermeasures in Corporate Statements. | Adriana Eufrosina Bora, Pierre-Luc St-Charles, Mirko Bronzi, Arsne Fansi Tchango, Bruno Rousseau, Kerrie L. Mengersen |
| 2025 | Breaking Neural Network Scaling Laws with Modularity. | Akhilan Boopathy, Sunshine Jiang, William Yue, Jaedong Hwang, Abhiram Iyer, Ila R. Fiete |
| 2025 | Revisiting Convolution Architecture in the Realm of DNA Foundation Models. | Yu Bo, Weian Mao, Yanjun Shao, Weiqiang Bai, Peng Ye, Xinzhu Ma, Junbo Zhao, Hao Chen, Chunhua Shen |
| 2025 | Shallow diffusion networks provably learn hidden low-dimensional structure. | Nicholas Matthew Boffi, Arthur Jacot, Stephen Tu, Ingvar M. Ziemann |
| 2025 | Linear combinations of latents in generative models: subspaces and beyond. | Erik Bodin, Alexandru I. Stere, Dragos D. Margineantu, Carl Henrik Ek, Henry Moss |
| 2025 | Depth Pro: Sharp Monocular Metric Depth in Less Than a Second. | Alexey Bochkovskiy, Amal Delaunoy, Hugo Germain, Marcel Santos, Yichao Zhou, Stephan R. Richter, Vladlen Koltun |
| 2025 | End-to-end Learning of Gaussian Mixture Priors for Diffusion Sampler. | Denis Blessing, Xiaogang Jia, Gerhard Neumann |
| 2025 | Underdamped Diffusion Bridges with Applications to Sampling. | Denis Blessing, Julius Berner, Lorenz Richter, Gerhard Neumann |
| 2025 | u-μP: The Unit-Scaled Maximal Update Parametrization. | Charlie Blake, Constantin Eichenberg, Josef Dean, Lukas Balles, Luke Yuri Prince, Bjrn Deiseroth, Andrs Felipe Cruz-Salinas, Carlo Luschi, Samuel Weinbach, Douglas Orr |
| 2025 | Scaling Optimal LR Across Token Horizons. | Johan Bjorck, Alon Benhaim, Vishrav Chaudhary, Furu Wei, Xia Song |
| 2025 | Efficient Active Imitation Learning with Random Network Distillation. | Emilien Bir, Anthony Kobanda, Ludovic Denoyer, Rmy Portelas |
| 2025 | Decoupling Angles and Strength in Low-rank Adaptation. | Massimo Bini, Leander Girrbach, Zeynep Akata |
| 2025 | Looking Inward: Language Models Can Learn About Themselves by Introspection. | Felix Jedidja Binder, James Chua, Tomek Korbak, Henry Sleight, John Hughes, Robert Long, Ethan Perez, Miles Turpin, Owain Evans |
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Comparable venues
Other A*/A conferences filed under the same field of research.
- A*ICMLInternational Conference on Machine Learning
- 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)