Felix's Library | Category: ml

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Computational Methods for Electromagnetic Inverse Scattering

Computational Methods for Electromagnetic Inverse Scattering

Entropy and Diversity: The Axiomatic Approach

Entropy and Diversity: The Axiomatic Approach

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

Stefano V. Albrecht & Filippos Christianos & Lukas Schäfer

Theory and Computation of Electromagnetic Fields

Theory and Computation of Electromagnetic Fields

Category: ml

Pattern Recognition and Machine Learning: Solutions to Exercises Web-Edition

Pattern Recognition and Machine Learning: Solutions to Exercises ...

Markus Svensén & Christopher M. Bishop

Computer Vision: Models, Learning, and Inference

Computer Vision: Models, Learning, and Inference

Simon J. D. Prince

Physics-based Deep Learning

Physics-based Deep Learning

N. Thuerey, B. Holzschuh, P. Holl, G. Kohl, M. Lino, Q. Liu, ...

Physics-based Deep Learning

Physics-based Deep Learning

N. Thuerey, B. Holzschuh, P. Holl, G. Kohl, M. Lino, Q. Liu, ...

Machine Learning, Second Edition: A Probabilistic Perspective

Machine Learning, Second Edition: A Probabilistic Perspective

Kevin P. Murphy

Statistical Rethinking: A Bayesian Course With Examples in R and STAN

Statistical Rethinking: A Bayesian Course With Examples in R ...

Richard McElreath

Statistical Rethinking: A Bayesian Course With Examples in R and STAN

Statistical Rethinking: A Bayesian Course With Examples in R ...

Richard McElreath

Probabilistic Graphical Models: Principles and Techniques

Probabilistic Graphical Models: Principles and Techniques

Daphne Koller & Nir Friedman

Probabilistic Graphical Models: Principles and Techniques

Probabilistic Graphical Models: Principles and Techniques

Daphne Koller & Nir Friedman

Non-Convex Optimization for Machine Learning

Non-Convex Optimization for Machine Learning

Prateek Jain & Purushottam Kar

Non-Convex Optimization for Machine Learning

Non-Convex Optimization for Machine Learning

Prateek Jain & Purushottam Kar

Pen and Paper Exercises in Machine Learning

Pen and Paper Exercises in Machine Learning

Michael U. Gutmann

Hyperparameter Optimization in Machine Learning

Hyperparameter Optimization in Machine Learning

Luca Franceschi

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning

Christopher M. Bishop

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning

Christopher M. Bishop

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

Stefano V. Albrecht & Filippos Christianos & Lukas Schäfer

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

Stefano V. Albrecht & Filippos Christianos & Lukas Schäfer

Matrix Calculus (for Machine Learning and Beyond)

Matrix Calculus (for Machine Learning and Beyond)

Alan Edelman, Steven G. Johnson