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Video World Models

Video diffusion models can generate stunning short clips, but building true world simulators requires a fundamental shift. This post explores how recent advances in causal attention, distribution matching distillation, and...

Training an EBM with Contrastive Divergence
Training an EBM with Contrastive Divergence

Interactive notebook providing a hands-on tutorial on training a simple EBM on synthetic datasets using the TorchEBM library. Covers energy functions, Langevin Dynamics for sampling, and Contrastive Divergence.

Hamiltonian Mechanics

Hamiltonian mechanics is a way to describe how physical systems, like planets or pendulums, move over time, focusing on energy rather than just forces. By reframing complex dynamics through energy lenses, this 19th-century physics framework now powers cutting-edge generative AI.

The Map Of Transformers
The Map Of Transformers

A broad overview of Transformers research covering the landscape of transformer architectures, their applications, and the evolution of attention mechanisms in deep learning.

Transformers in Action: Attention Is All You Need
Transformers in Action: Attention Is All You Need

A brief survey, illustration, and implementation guide to understanding the transformer architecture and attention mechanisms that revolutionized natural language processing.

Rethinking Thinking: How Do Attention Mechanisms Actually Work?
Rethinking Thinking: How Do Attention Mechanisms Actually Work?

The brain, the mathematics, and DL – research frontiers exploring the intersection of neuroscience and attention mechanisms in artificial intelligence.