David Wessels
14.2K posts
@Dafidofff
PhD candidate w/ @erikjbekkers & @egavves interested in Geometric Deep Learning and Generative Modelling at @AmlabUva
You like discrete diffusion, but it's too slow? 🥀 You like test-time inference, but it's for continuous methods? 😩 We fixed it. Introducing Categorical Flow Maps: continuously sample discrete data in a single step 🚀💫 How? 🧵⬇️ 💪 Co-led with @FEijkelboom, @daan_roos_
Why do video models handle motion so poorly? It might be lack of motion equivariance. Very excited to introduce: Flow Equivariant RNNs (FERNNs), the first sequence models to respect symmetries over time. Paper: arxiv.org/abs/2507.14793 Blog: kempnerinstitute.harvard.edu/research/deepe… 1/🧵
🌍 From earthquake prediction to robot navigation - what connects them? Eikonal equations! We developed E-NES: a neural network that leverages geometric symmetries to solve entire families of velocity fields through group transformations. Grid-free and scalable! 🧵👇
We've raised $100M from Kleiner Perkins, Index Ventures, Lightspeed, and NVIDIA. Today we're introducing Sonic-3 - the state-of-the-art model for realtime conversation. What makes Sonic-3 great: - Breakthrough naturalness - laughter and full emotional range - Lightning fast -
Clifford Algebra Neural Networks are undeservedly dismissed for being too slow, but they don't have to be! 🚀Introducing **flash-clifford**: a hardware-efficient implementation of Clifford Algebra NNs in Triton, featuring the fastest equivariant primitives that scale.
