31 citations · 40 across the 30 of their papers we have counts for
7 papers · 1 filter
Discrete Flow Maps
Peter Potaptchik, Jason Yim, Adhi Saravanan +3
The sequential nature of autoregressive next-token prediction imposes a fundamental speed limit on large language models. While continuous flow models offer a path to parallel gene…
Probing the Geometry of Diffusion Models with the String Method
Elio Moreau, Florentin Coeurdoux, Grégoire Ferre +1
Understanding the geometry of learned distributions is fundamental to improving and interpreting diffusion models, yet systematic tools for exploring their landscape remain limited…
MGD: Moment Guided Diffusion for Maximum Entropy Generation
Etienne Lempereur, Nathanaël Cuvelle--Magar, Florentin Coeurdoux +2
Generating samples from limited information is a fundamental problem across scientific domains. Classical maximum entropy methods provide principled uncertainty quantification from…
Scale-Adaptive Generative Flows for Multiscale Scientific Data
Yifan Chen, Eric Vanden-Eijnden
Flow-based generative models can face numerical challenges on scientific data with multiscale Fourier spectra, often producing large errors at fine scales. We approach this problem…
Lipschitz-Guided Design of Interpolation Schedules in Generative Models
Yifan Chen, Eric Vanden-Eijnden, Jiawei Xu
We study the design of interpolation schedules in flow and diffusion-based generative models from both statistical and numerical perspectives. Within the stochastic interpolants fr…
FEAT: Free energy Estimators with Adaptive Transport
Jiajun He, Yuanqi Du, Francisco Vargas +4
We present Free energy Estimators with Adaptive Transport (FEAT), a novel framework for free energy estimation -- a critical challenge across scientific domains. FEAT leverages lea…
Analysis of learning a flow-based generative model from limited sample complexity
Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden +1
We study the problem of training a flow-based generative model, parametrized by a two-layer autoencoder, to sample from a high-dimensional Gaussian mixture. We provide a sharp end-…