Physics-based Deep Learning
N. Thuerey, B. Holzschuh, P. Holl, G. Kohl, M. Lino, Q. Liu, ...
Pattern Recognition and Machine Learning
Christopher M. Bishop
The Design of Approximation Algorithms
David P. Williamson & David B. Shmoys
Information Geometry and Its Applications
Shun-Ichi Amari
Matrix Calculus (for Machine Learning and Beyond)
Alan Edelman, Steven G. Johnson
Hyperparameter Optimization in Machine Learning
Luca Franceschi
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
Stefano V. Albrecht & Filippos Christianos & Lukas Schäfer
Non-Convex Optimization for Machine Learning
Prateek Jain & Purushottam Kar
Statistical Rethinking: A Bayesian Course With Examples in R ...
Richard McElreath
Probabilistic Graphical Models: Principles and Techniques
Daphne Koller & Nir Friedman
Computer Vision: Models, Learning, and Inference
Simon J. D. Prince
Pen and Paper Exercises in Machine Learning
Michael U. Gutmann
Machine Learning, Second Edition: A Probabilistic Perspective
Kevin P. Murphy
Pattern Recognition and Machine Learning: Solutions to Exercises ...
Markus Svensén & Christopher M. Bishop