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1
Introduction
2
Symmetries
3
Observation
4
Math
5
Example
6
Equivalence
7
Len
8
Basic tools
9
Composition
10
Tensor Product
11
Reducible Representation
12
CLG Theorem
13
Linear Mixing
14
Network Equivalent
15
Data Efficiency
16
Open Question
17
Discussion
Description:
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.

Learning Geometry and 3D Symmetries - Day 1

Valence Labs
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