Explore a 59-minute video lecture on Deep Distillation and Explainable Neural Networks (ENNs) featuring Milo Lin, Assistant Professor at UT Southwest Medical Center. Delve into the promising neurosymbolic architecture of ENNs, which employs a bottom-up training procedure allowing direct translation into code. Gain insights on explainability and biological inspiration in AI, understand the ENN architecture and training process, and learn about deep distillation techniques. Examine a practical application through the Game of Life experiment. Access references to published research on Deep Distillation and ENNs in Nature journals. Discover this content as part of the Neuro Symbolic Channel, which offers tutorials, courses, and research findings on the intersection of symbolic methods and deep learning in artificial intelligence.
Deep Distillation and Explainable Neural Networks (ENNs) - Lecture
Overview
Syllabus
Introduction
On explainability and biological inspiration
ENN architecture and training
Deep distillation
Game of life experiment
Taught by
Neuro Symbolic
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