14 citations · 18 across the 4 of their papers we have counts for
4 papers
NAS-X: Neural Adaptive Smoothing via Twisting
Dieterich Lawson, Michael Li, Scott Linderman
Sequential latent variable models (SLVMs) are essential tools in statistics and machine learning, with applications ranging from healthcare to neuroscience. As their flexibility in…
Why think step by step? Reasoning emerges from the locality of experience
Ben Prystawski, Michael Y. Li, Noah D. Goodman
Humans have a powerful and mysterious capacity to reason. Working through a set of mental steps enables us to make inferences we would not be capable of making directly even though…
Gaussian Process Surrogate Models for Neural Networks
Michael Y. Li, Erin Grant, Thomas L. Griffiths
Not being able to understand and predict the behavior of deep learning systems makes it hard to decide what architecture and algorithm to use for a given problem. In science and en…
Minimax Optimal Conditional Density Estimation under Total Variation Smoothness
Michael Li, Matey Neykov, Sivaraman Balakrishnan
This paper studies the minimax rate of nonparametric conditional density estimation under a weighted absolute value loss function in a multivariate setting. We first demonstrate th…