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Generative Models

Generative Models

Learn latent-variable models, diffusion, flow matching, and predictive representation learning in a coherent order.

Intermediate5 visual deep dives
1

Variational Autoencoders: Principles, Derivations, and Applications

Variational auto-encoders

84 min read›2

Diffusion Models and Flow Matching: From Score-Based Diffusion to Continuous Normalizing Flows

Diffusion and flow-matching

87 min read›3

I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture

Self-supervised vision model for learning image representations.

87 min read›4

World Models: Learning to Dream for Efficient Reinforcement Learning

World Models

84 min read›5

LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architectures from Pixels

Stable JEPA-based world model that learns and plans from raw pixels.

45 min read›