5 papers · 1 filter
Barron Optimal Transport I: Generative Modeling
Evan Dogariu, Joan Bruna
Motivated by recent applications in generative modeling and sampling, we introduce a framework for optimal measure transport where cost captures the notion of neural network comple…
Universal Learning of Nonlinear Dynamics
Evan Dogariu, Anand Brahmbhatt, Elad Hazan
We study the fundamental problem of one-step prediction of a marginally stable unknown nonlinear dynamical system. We describe an algorithm for this problem, based on the technique…
Provable Length Generalization in Sequence Prediction via Spectral Filtering
Annie Marsden, Evan Dogariu, Naman Agarwal +3
We consider the problem of length generalization in sequence prediction. We define a new metric of performance in this setting -- the Asymmetric-Regret -- which measures regret aga…
FutureFill: Fast Generation from Convolutional Sequence Models
Naman Agarwal, Xinyi Chen, Evan Dogariu +6
We address the challenge of efficient auto-regressive generation in sequence prediction models by introducing FutureFill, a general-purpose fast generation method for any sequence…
Flash STU: Fast Spectral Transform Units
Y. Isabel Liu, Windsor Nguyen, Yagiz Devre +3
Recent advances in state-space model architectures have shown great promise for efficient sequence modeling, but challenges remain in balancing computational efficiency with model…