5 papers
ABC: Any-Subset Autoregression via Non-Markovian Diffusion Bridges in Continuous Time and Space
Gabe Guo, Thanawat Sornwanee, Lutong Hao +3
Generating continuous-time, continuous-space stochastic processes (e.g., videos, weather forecasts) conditioned on partial observations (e.g., first and last frames) is a fundament…
A Theory of Generalization in Deep Learning
Elon Litman, Gabe Guo
We present a non-asymptotic theory of generalization in deep learning where the empirical neural tangent kernel partitions the output space. In directions corresponding to signal,…
You Need Better Attention Priors
Elon Litman, Gabe Guo
We generalize the attention mechanism by viewing it through the lens of Entropic Optimal Transport, revealing that standard attention corresponds to a transport problem regularized…
Reviving Any-Subset Autoregressive Models with Principled Parallel Sampling and Speculative Decoding
Gabe Guo, Stefano Ermon
In arbitrary-order language models, it is an open question how to sample tokens in parallel from the correct joint distribution. With discrete diffusion models, the more tokens the…
Ab Initio Structure Solutions from Nanocrystalline Powder Diffraction Data
Gabe Guo, Tristan Saidi, Maxwell Terban +3
A major challenge in materials science is the determination of the structure of nanometer sized objects. Here we present a novel approach that uses a generative machine learning mo…