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ICLR 2025

The Thirteenth International Conference on Learning Representations

Singapore EXPO

Thu Apr 24 – Mon Apr 28th, 2025

Registration


Click on Photo - Link to Singapore EXPO

Announcements

  • Childcare available onsite - Sign up Here
     
  • Applications for Financial Assistance to attend ICLR 2025 are now Open. All are eligible, but student and new contributors to ICLR 2025 will be prioritized.
     
  • The Hotel Reservations available Here.  Special group pricing has been made for ICLR attendees.  Please make your reservations through this link only.   For hotel reservation support, please email at ICLR@resiada.com or call +1 833-628-6179.  Our support office is open from 9:00 a.m. to 6:00 p.m. EST. Monday through Friday.
     
  • Sponsor / Exhibitor applications are Open
     
  • BEWARE of predatory ICLR conferences being promoted through the World Academy of Science, Engineering and Technology organization.

Important Dates

Full Paper Submission Deadline Oct 01 '24 (Anywhere on Earth)
Financial Assistance Application Deadline Mar 02 '25 (Anywhere on Earth)
Volunteer Application Deadline Mar 09 '25 (Anywhere on Earth)
Financial Assistance Application Notification Mar 09 '25 (Anywhere on Earth)
Early Registration Deadline Mar 15 '25 (Anywhere on Earth)
All dates

Timezone:

About Us

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