The Eleventh International Conference on Learning Representations
Mon May 1 — Fri May 5
We are very excited to be holding the ICLR 2023 annual conference in Kigali, Rwanda this year from May 1-5, 2023. The conference will be located at the beautiful Kigali Convention Centre / Radisson Blu Hotel location which was recently built and opened for events and visitors in 2016. The Kigali Convention Centre is located 5 kilometers from the Kigali International Airport.
The in-person conference will also provide viewing and virtual participation for those attendees who are unable to come to Kigali, including a static virtual exhibitor booth for most sponsors.
We look forward to answering any questions you may have, and hopefully seeing you in Kigali.
Latest ICLR Blog Entries [ All Entries ]
Apr 24, 2023 Announcing ICLR 2023 Office Hours
Apr 13, 2023 Ethics Review Process for ICLR 2023
Apr 06, 2023 Announcing Notable Reviewers and Area Chairs at ICLR 2023
Mar 21, 2023 Announcing the ICLR 2023 Outstanding Paper Award Recipients
Feb 18, 2023 Get Ready for ICLR 2023
Feb 14, 2023 Announcing ICLR 2023 Keynote Speakers
|Conference Sessions and Workshops||Mon May 1st through Fri the 5th|
|Virtual Only Pass||Mon May 1st through Fri the 5th|
|Thursday Workshop 1 Day Pass||Thu May 4th|
|Friday Workshop 1 Day Pass||Fri May 5th|
|Sponsor Portal Close||Jun 15 '23 (Anywhere on Earth)|
|All dates »||
The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.
ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics.
Participants at ICLR span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.
A non-exhaustive list of relevant topics explored at the conference include:
- unsupervised, semi-supervised, and supervised representation learning
- representation learning for planning and reinforcement learning
- representation learning for computer vision and natural language processing
- metric learning and kernel learning
- sparse coding and dimensionality expansion
- hierarchical models
- optimization for representation learning
- learning representations of outputs or states
- optimal transport
- theoretical issues in deep learning
- societal considerations of representation learning including fairness, safety, privacy, and interpretability, and explainability
- visualization or interpretation of learned representations
- implementation issues, parallelization, software platforms, hardware
- climate, sustainability
- applications in audio, speech, robotics, neuroscience, biology, or any other field