Curated resources

Books

• Algorithms for Optimization, Kochenderfer & Wheeler
• Algorithms of Reinforcement Learning, Szepesvári
• Artificial Intelligence: A Modern Approach, Russell & Norvig
• Computer Systems: A Programmer’s Perspective, Bryant & O’Hallaron
• Data-driven Science and Engineering, Brunton & Kutz
• Deep Learning: Foundations and Concepts, Bishop & Bishop
• Mathematical Foundations of Reinforcement Learning, Zhao
• Modern Robotics, Lynch & Park
• Principles of Robot Autonomy, Lorenzetti & Pavone
• Reinforcement Learning: A Comprehensive Overview, Murphy
• Reinforcement Learning: An Introduction, Sutton & Barto
• Robotic Manipulation, Tedrake
• The Little Book of Deep Learning, Fleuret
• Underactuated Robotics, Tedrake

Articles

• A Standard Rigid Transformation Notation Convention for Robotics Research, Nadeau
• Drake: Notation Basics, Drake C++ Documentation
• Formal Algorithms for Transformers, Phuong & Hutter
• Hints and Principles for Computer System Design, Lampson
• Neural Circuit Diagrams, Abbott

Talks

• Robotics Seminar, Robotics @ MIT
• Visualizing transformers and attention, Grant Sanderson