2027 Conference Skip to yearly menu bar Skip to main content Main Navigation ICLR Help/FAQ Contact ICLR Create Profile Code of Conduct Journal To Conference Track Diversity & Inclusion Proceedings at OpenReview Future Meetings Press Exhibitor Information ICLR Blog ICLR Twitter About ICLR Downloads Privacy Policy Reset Password My Stuff Login Select Year: (2027) 2027 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 Dates Calls Call for Papers Guides Author Guide Area Chair Guide Senior Area Chair Guide Reviewer Guide AI Policy for Reviewers AI Policy for Authors ICLR 2027 The Fifteenth International Conference on Learning Representations California April 26-30, 2027 Register starting Apr 26 12 AM PDT Pricing Cancellation Policy Quick Links ICLR 2026 Call for Papers Latest Announcements ICLR 2027 Reviewer Self-Nomination Form    July 28: Call for papers is posted with associated author, reviewer, AC, and SAC guides under the Guides menu above.   Official Hotel Group Rates Note:  ICLR has secured discounted group hotel rates, and we ask that all reservations be made through the official Housing Portal, which will be posted six months prior to the conference. Booking elsewhere undermines the room-block commitments required to bring ICLR to any host city — commitments that keep rates low for everyone. Hotels will not confirm space directly and are aware of this policy. It also protects you: the official portal is the only guaranteed way to access approved hotels at conference rates, rather than risking a fraudulent or unauthorized site. Venue Venue information will be posted here The conference is a five-day multi-track event with a mix of invited talks, oral paper presentations, and poster sessions. The fourth and fifth day are workshops. Book your room (late October) Exhibitors We thank our exhibitors for all their support! Information on becoming an exhibitor will be posted here. See 2026 Exhibitors. View Exhibitors Contact Us Exhibitor Info » Important Dates Abstract Deadline Sep 18 '26 (Anywhere on Earth) Paper Deadline Sep 25 '26 (Anywhere on Earth) Reviews Released Nov 05 '26 * Final Decisions Dec 16 '26 * View All Dates Timezone: About the Conference 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. ICLR is one of the fastest growing artificial intelligence conferences in the world. Participants at ICLR span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs. The rapidly developing field of deep learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. ICLR takes a broad view of the field and includes topics such as feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization. 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 Metric Learning and Kernel Learning Sparse Coding and Dimensionality Expansion Hierarchical Models Optimization for Representation Learning Learning Representations of Outputs or States Implementation Issues, Parallelization, Software Platforms, Hardware Applications in Vision, Audio, Speech, Natural Language Processing, Robotics, Neuroscience, or Any Other Field The ICLR Logo above may be used on presentations. Right-click and choose download. It is a vector graphic and may be used at any scale. Useful links About ICLR Sponsor / Exhibitor Information Press Contact 2710 E Corridor Dr, Appleton WI 54913 Email Phone: +1-920-268-4789 ICLR Proceedings at OpenReview