Review: Symbolic regression (Miles Cranmer)

Review - Machine Learning and Bayesian inference (Jens Jasche)

Python Symbolic Regression (PySR) [Physics Informed Machine Learning]

Interpretability via Symbolic Distillation

Stephen Wolfram - Where the Computational Paradigm Leads (in Physics, Tech, AI, Biology, Math, ...)

Visualizing transformers and attention | Talk for TNG Big Tech Day '24

Symbolic Regression for Model Discovery in Python and Julia

First lecture on Bayesian Deep Learning and Uncertainty Quantification

Workshop 2: An Introduction to Symbolic Regression with PySR and SymbolicRegression.jl

ICLR 2021 Keynote - "Geometric Deep Learning: The Erlangen Programme of ML" - M Bronstein

Deep Symbolic Regression: Recovering Math Expressions from Data via Risk-Seeking Policy Gradients

Miles Cranmer - The Next Great Scientific Theory is Hiding Inside a Neural Network (April 3, 2024)

KAN: Kolmogorov-Arnold Networks

Interpretable Deep Learning for New Physics Discovery

The Potential for AI in Science and Mathematics - Terence Tao

Symbolic Regression and Program Induction: Lars Buesing

Converting Neural Networks to Symbolic Models

The Anatomy of a Dynamical System

Interpretable Machine Learning with SymbolicRegression.jl | Miles Cranmer | JuliaCon 2023

Lenka Zdeborová - Statistical Physics of Machine Learning (May 1, 2024)

11 Discovering Equations using Machine Learning