Dieterich Lawson Headshot

Dieterich Lawson

I am PhD student in computer science at Stanford University, advised by Scott Linderman. My recent work focuses on mechanistic models for neural data and learning algorithms for better statistical inference.


Selected publications

(full list)

Energy-Inspired Models: Learning with Sampler-Induced Distributions
Dieterich Lawson*, George Tucker*, Bo Dai, and Rajesh Ranganath
Neural Information Processing Systems (NeurIPS), 2019

Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
George Tucker, Dieterich Lawson, Shixiang Gu, Chris J Maddison
International Conference on Learning Representations (ICLR), 2019

Filtering Variational Objectives
Chris J. Maddison*, Dieterich Lawson*, George Tucker*, Nicolas Heess, Mohammad Norouzi, Andriy Mnih, Arnaud Doucet, and Yee Whye Teh
Neural Information Processing Systems (NeurIPS), 2017

Rebar: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker, Andriy Mnih, Chris J Maddison, Dieterich Lawson, Jascha Sohl-Dickstein
NeurIPS 2017

Learning Hard Alignments with Variational Inference
Dieterich Lawson*, Chung-Cheng Chiu*, George Tucker*, Colin Raffel, Kevin Swersky, and Navdeep Jaitly
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018