Deep Generative Modeling

Jakub M. Tomczak is an associate professor and the head of the Generative AI group at the Eindhoven University of Technology (TU/e). Before joining the TU/e, he was an assistant professor at Vrije Universiteit Amsterdam, a deep learning researcher (Engineer, Staff) in Qualcomm AI Research in Amsterdam, a Marie Sklodowska-Curie individual fellow in Prof. Max Welling's group at the University of Amsterdam, and an assistant professor and a postdoc at the Wroclaw University of Technology. His main research interests include ML, DL, deep generative modeling (GenAI), and Bayesian inference, with applications to image/text processing, Life Sciences, Molecular Sciences, and quantitative finance. He serves as an action editor of "Transactions of Machine Learning Research", and an area chair of major AI conferences (e.g., NeurIPS, ICML, AISTATS). He is a program chair of NeurIPS 2024. He is the author of the book entitled "Deep Generative Modeling", the first comprehensive book on Generative AI. He is also the founder of Amsterdam AI Solutions.

• Chapter 1 Why Deep Generative Modeling?.-  Chapter 2 Probabilistic modeling: From Mixture Models to Probabilistic Circuits.-  Chapter 3 Autoregressive Models.- Chapter 4 Flow-based Models.-  Chapter 5 Latent Variable Models.-  Chapter 6 Hybrid Modeling.-  Chapter 7 Energy-based Models.- Chapter 8 Generative Adversarial Networks.- Chapter 9 Score-based Generative Models.-  Chapter 10 Deep Generative Modeling for Neural Compression.-  Chapter 11 From Large Language Models to Generative AI.