Deep Generative Modeling - MIT 6.S191 Lecture 4
Explore deep generative modeling, including autoencoders, VAEs, GANs, and recent advances. Learn about latent variables, training techniques, and applications in AI-driven content creation and data analysis.
Latent User Intent Modeling in Recommender Systems
Explore latent variable models for capturing user intents in recommender systems, enhancing understanding beyond item-level interactions.
A Cookbook for Deep Continuous-Time Predictive Models
Explore deep continuous-time predictive models for irregularly-sampled time series, from feedforward approaches to latent-variable stochastic differential equations.
Deep Generative Models - Lectures 2 and 3
Explore advanced deep generative models with expert insights on latest techniques, applications, and theoretical foundations in probabilistic AI.
Introduction to Deep Generative Models
Explore deep generative models, their applications, and underlying principles in this comprehensive introduction by Jes Frellen at the Nordic Probabilistic AI School.
Deep Generative Models 1 - Lecture
Explore deep generative models with experts, covering fundamental concepts and advanced techniques in probabilistic AI. Gain insights into cutting-edge research and applications.