Awesome Machine Learning Monographs

...and book chapters

Neurosymbolic and Neurocausal Learning

• Neuro-Causal Models (Aragam and Ravikumar 2024)
• Causal Fairness Analysis - A Causal Toolkit for Fair Machine Learning (Plečko and Bareinboim 2024)
• Neurosymbolic AI for Reasoning Over Knowledge Graphs: A Survey (DeLong et al. 2023)
• Neurosymbolic Programming (Chaudhuri et al. 2021)

Conformal Prediction

• Conformal Prediction: A Gentle Introduction (Angelopoulos et al. 2022)
• A Tutorial on Conformal Prediction (Shafer and Vovk 2008)

Distributed Learning

• Advances and Problems in Federated Learning (Kairouz et al. 2019)

Misc.

• Foundation Models for Natural Language Processing (Paaß and Giesselbach 2023) -- technically a book but pick any chapter 🤪
• An Introduction to Variational Autoencoders (Kingma and Welling 2019)
• Algorithms for Reinforcement Learning (Szepesvàri 2009)
• Learning Deep Architectures for AI (Bengio 2009)