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Automatic Differentiation Library
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
Source-to-Source Debuggable Derivatives in Pure Python
A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
A simple library for creating complex neural networks
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.
Tensors and differentiable operations (like TensorFlow) in Rust
Softcopy of Engineering Books. If you want a book{s} to be taken down, please contact me.
An experimental computer algebra system written in Go