International Conference on Learning Representations
The International Conference on Learning Representations (ICLR) is the premier gathering of researchers dedicated to advancing representation learning and deep learning. Founded in 2013 by Yann LeCun and Yoshua Bengio, ICLR pioneered an open peer review process and has grown into one of the fastest-growing AI conferences in the world. It publishes cutting-edge research spanning machine vision, natural language processing, speech recognition, robotics, computational biology, and other deep learning application areas, drawing participants from academia and industry globally.
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Theory of Change
ICLR does not have an explicit AI safety or existential risk theory of change. As a general machine learning conference, it accelerates the development and dissemination of deep learning research across the global research community. It is relevant to AI safety indirectly insofar as it is a venue where AI safety papers are submitted and discussed, and where norms and standards in the ML research community are shaped. However, ICLR itself is neutral with respect to safety versus capabilities.
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Details
- Last Updated
- Apr 2, 2026, 10:10 PM UTC
- Created
- Mar 20, 2026, 2:35 AM UTC