Overview
The International Conference on Learning Representations is the premier gathering of academic and industrial researchers, entrepreneurs, engineers, and graduate and postdoc students dedicated to the advancement of representation learning, or deep learning. Research presented and published at ICLR covers 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.
Accepted publications
Workshops
ICLR 2022 Workshop on DL4C
April 29
ICLR 2022 Workshop on Deep Generative Models for Highly Structured Data
Unknown date
ICLR 2022 Workshop on objects, structure and causality
Unknown date
Related content
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May 03, 2021Workshop at ICLR 2021 unites communities investigating synthetic data generation to improve machine learning and protect privacy.
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April 29, 2021Amazon Scholar Aravind Srinivasan on the importance of machine learning for real-time and offline resource management.
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April 06, 2021Ability to balance parameter size and effectiveness could be “extremely useful” in reducing parameter size of deep-learning models.
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May 13, 2020Watch the ICLR 2020 keynote presentation by Michael I. Jordan, Amazon scholar and UC Berkeley professor.