Dieterich Lawson

According to our database, Dieterich Lawson authored at least 15 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

NAS-X: Neural Adaptive Smoothing via Twisting.

Dieterich Lawson, Michael Li, Scott W. Linderman

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

The Neural Testbed: Evaluating Joint Predictions.

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Dieterich Lawson, Botao Hao, Brendan O'Donoghue, Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SIXO: Smoothing Inference with Twisted Objectives.

Dieterich Lawson, Allan Raventós, Andrew Warrington, Scott W. Linderman

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Botao Hao, Morteza Ibrahimi, Dieterich Lawson, Xiuyuan Lu, Brendan O'Donoghue, Benjamin Van Roy

CoRR, 2021

2019

Energy-Inspired Models: Learning with Sampler-Induced Distributions.

Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives.

George Tucker, Dieterich Lawson, Shixiang Gu, Chris J. Maddison

Proceedings of the 7th International Conference on Learning Representations, 2019

Revisiting Auxiliary Latent Variables in Generative Models.

Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

2018

Learning Hard Alignments with Variational Inference.

Dieterich Lawson, Chung-Cheng Chiu, George Tucker, Colin Raffel, Kevin Swersky, Navdeep Jaitly

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

An online sequence-to-sequence model for noisy speech recognition.

Chung-Cheng Chiu, Dieterich Lawson, Yuping Luo, George Tucker, Kevin Swersky, Ilya Sutskever, Navdeep Jaitly

CoRR, 2017

REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models.

George Tucker, Andriy Mnih, Chris J. Maddison, Dieterich Lawson, Jascha Sohl-Dickstein

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Filtering Variational Objectives.

Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Mohammad Norouzi, Andriy Mnih, Arnaud Doucet, Yee Whye Teh

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Training a Subsampling Mechanism in Expectation.

Colin Raffel, Dieterich Lawson

Proceedings of the 5th International Conference on Learning Representations, 2017

Changing Model Behavior at Test-time Using Reinforcement Learning.

Augustus Odena, Dieterich Lawson, Christopher Olah

Proceedings of the 5th International Conference on Learning Representations, 2017

Particle Value Functions.

Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Arnaud Doucet, Andriy Mnih, Yee Whye Teh

Proceedings of the 5th International Conference on Learning Representations, 2017

2011

The tablecast data publishing protocol.

Ka-Ping Yee, Dieterich Lawson, Dominic König, Dale Zak

Proceedings of the 8th Proceedings of the International Conference on Information Systems for Crisis Response and Management, 2011