Machine Learning Symmetry

01/23/2022
by   Shailesh Lal, et al.
0

We review recent work in machine learning aspects of conformal field theory and Lie algebra representation theory using neural networks.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/14/2021

Machine learning a manifold

We propose a simple method to identify a continuous Lie algebra symmetry...
research
09/15/2021

Automatic Symmetry Discovery with Lie Algebra Convolutional Network

Existing equivariant neural networks for continuous groups require discr...
research
01/15/2021

Machine-Learning Mathematical Structures

We review, for a general audience, a variety of recent experiments on ex...
research
05/01/2016

Directional Statistics in Machine Learning: a Brief Review

The modern data analyst must cope with data encoded in various forms, ve...
research
03/08/2023

A General Theory of Correct, Incorrect, and Extrinsic Equivariance

Although equivariant machine learning has proven effective at many tasks...
research
02/11/2015

How to show a probabilistic model is better

We present a simple theoretical framework, and corresponding practical p...
research
10/14/2022

Representation Theory for Geometric Quantum Machine Learning

Recent advances in classical machine learning have shown that creating m...

Please sign up or login with your details

Forgot password? Click here to reset