# ICLR — International Conference on Learning Representations

- **Submission deadline**: 2026-09-18
- **Notification date**: 2026-12-16
- **Conference date**: 2027-04-26
- **Location**: San Francisco, California, USA
- **Rankings**: CCF A · CORE A*
- **Conference Partner Index**: 89.3/100 (ranked #80, confidence 1.00, algorithm 1.1) — how this is computed: https://www.myhuiban.com/ranking
- **Trackers**: 287
- **Attendees**: 20
- **Canonical page**: https://www.myhuiban.com/conference/2350

## Acceptance history

| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| 2025 | 11565 | 3708 | 32.1% |
| 2024 | 7304 | 2250 | 30.8% |
| 2023 | 4956 | 1574 | 31.8% |
| 2022 | 3328 | 1095 | 32.9% |
| 2021 | 2997 | 860 | 28.7% |
| 2020 | 2594 | 687 | 26.5% |
| 2019 | 1591 | 500 | 31.4% |
| 2018 | 981 | 314 | 32% |
| 2017 | 507 | 198 | 39.1% |

## Past editions

| Year | Deadline | Conference date | Location |
|---|---|---|---|
| 2026 | 2025-09-19 | 2026-04-24 | Singapore |

## Call for papers

Subject Areas We consider a broad range of subject areas including feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, uncertainty quantification and issues regarding large-scale learning and non-convex optimization, as well as applications in vision, audio, speech, language, music, robotics, games, healthcare, biology, sustainability, economics, ethical considerations in ML, and others. A non-exhaustive list of relevant topics: unsupervised, self-supervised, semi-supervised, and supervised representation learning transfer learning, meta learning, and lifelong learning reinforcement learning representation learning for computer vision, audio, language, and other modalities metric learning, kernel learning, and sparse coding probabilistic methods (Bayesian methods, variational inference, sampling, UQ, etc.) generative models causal reasoning optimization learning theory learning on graphs and other geometries & topologies societal considerations including fairness, safety, privacy visualization or interpretation of learned representations datasets and benchmarks infrastructure, software libraries, hardware, etc. neurosymbolic & hybrid AI systems (physics-informed, logic & formal reasoning, etc.) applications to robotics, autonomy, planning applications to neuroscience & cognitive science applications to physical sciences (physics, chemistry, biology, etc.) general machine learning (i.e., none of the above) Submissions will be double blind: reviewers cannot see author names when conducting reviews, and authors cannot see reviewer names. Having papers on arxiv is allowed per the dual submission policy outlined in the author guidelines.

## Related conferences

- SIGIR — International Conference on Research and Development in Information Retrieval — https://www.myhuiban.com/conference/141
- AAAI — AAAI Conference on Artificial Intelligence — https://www.myhuiban.com/conference/408
- CVPR — IEEE Conference on Computer Vision and Pattern Recognition — https://www.myhuiban.com/conference/407
- STOC — ACM Symposium on Theory of Computing — https://www.myhuiban.com/conference/359
- OSDI — USENIX Symposium on Operating Systems Design and Implementation — https://www.myhuiban.com/conference/358

## Related journals

- Engineering Applications of Artificial Intelligence — https://www.myhuiban.com/journal/209
- Pattern Recognition — https://www.myhuiban.com/journal/198
- Neural Networks — https://www.myhuiban.com/journal/197
- IEEE Transactions on Multimedia — https://www.myhuiban.com/journal/152
- World Wide Web — https://www.myhuiban.com/journal/122

---
Source: Conference Partner — https://www.myhuiban.com/conference/2350 (rankings reproduced from CCF / ICORE / QUALIS; data cached up to 1 hour)