Explore the fundamentals of geometry and 3D symmetries in this 45-minute lecture from the 2024 Machine Learning for Drug Discovery Summer School at Mila. Delve into topics such as symmetries, observations, mathematical concepts, and examples as presented by Mario Geiger from Valence Labs. Gain insights into equivalence, basic tools, composition, tensor products, and reducible representations. Examine the CLG Theorem, linear mixing, network equivalence, and data efficiency. Engage with open questions and participate in a discussion to deepen your understanding of these crucial concepts in machine learning for drug discovery.
Overview
Syllabus
Introduction
Symmetries
Observation
Math
Example
Equivalence
Len
Basic tools
Composition
Tensor Product
Reducible Representation
CLG Theorem
Linear Mixing
Network Equivalent
Data Efficiency
Open Question
Discussion
Taught by
Valence Labs