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Dieterich Lawson
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Cited by
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Rebar: Low-variance, unbiased gradient estimates for discrete latent variable models
G Tucker, A Mnih, CJ Maddison, J Lawson, J Sohl-Dickstein
Advances in Neural Information Processing Systems 30, 2017
3282017
Filtering variational objectives
CJ Maddison, D Lawson, G Tucker, N Heess, M Norouzi, A Mnih, ...
Advances in Neural Information Processing Systems, 6573-6583, 2017
2352017
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
G Tucker, D Lawson, S Gu, CJ Maddison
International Conference on Learning Representations (ICLR) 2019, 2018
1212018
Changing model behavior at test-time using reinforcement learning
A Odena, D Lawson, C Olah
International Conference on Learning Representations (ICLR) Workshops 2017, 2017
522017
Learning Hard Alignments with Variational Inference
D Lawson, CC Chiu, G Tucker, C Raffel, K Swersky, N Jaitly
IEEE International Conference on Acoustics, Speech and Signal Processing …, 2018
402018
Energy-Inspired Models: Learning with Sampler-Induced Distributions
D Lawson, G Tucker, B Dai, R Ranganath
Advances in Neural Information Processing Systems 32 (2019), 2019
372019
Twisted variational sequential monte carlo
D Lawson, G Tucker, CA Naesseth, C Maddison, RP Adams, YW Teh
Third workshop on Bayesian Deep Learning (NeurIPS), 2018
222018
Particle Value Functions
CJ Maddison, D Lawson, G Tucker, N Heess, A Doucet, A Mnih, YW Teh
International Conference on Learning Representations (ICLR) Workshops 2017, 2017
182017
The neural testbed: Evaluating joint predictions
I Osband, Z Wen, SM Asghari, V Dwaracherla, X Lu, M Ibrahimi, ...
Advances in Neural Information Processing Systems 35, 12554-12565, 2022
162022
Evaluating predictive distributions: Does Bayesian deep learning work?
I Osband, Z Wen, SM Asghari, X Lu, M Ibrahimi, V Dwaracherla, ...
92021
An online sequence-to-sequence model for noisy speech recognition
CC Chiu, D Lawson, Y Luo, G Tucker, K Swersky, I Sutskever, N Jaitly
arXiv preprint arXiv:1706.06428, 2017
82017
SIXO: Smoothing Inference with Twisted Objectives
D Lawson, A Raventós, A Warrington, S Linderman
Advances in Neural Information Processing Systems (NeurIPS) 36, 2022
52022
Training a subsampling mechanism in expectation
C Raffel, D Lawson
arXiv preprint arXiv:1702.06914, 2017
52017
Alternating direction method of multipliers implementation using Apache Spark
D Lawson
Stanford University: Stanford, CA, USA, 2014
52014
Recurrent neural networks for online sequence generation
CC Chiu, N Jaitly, JD Lawson, GJ Tucker
US Patent 11,625,572, 2023
32023
Image captioning with attention
B Rister, D Lawson
IEEE Computation Conference, 2016
22016
NAS-X: neural adaptive smoothing via twisting
D Lawson, M Li, S Linderman
Advances in Neural Information Processing Systems 36, 2024
12024
Neural Adaptive Smoothing via Twisting
MY Li, D Lawson, S Linderman
Fifth Symposium on Advances in Approximate Bayesian Inference, 0
1
Adjusting neural network resource usage
AQ Odena, JD Lawson
US Patent App. 18/487,802, 2024
2024
Adjusting neural network resource usage
AQ Odena, JD Lawson
US Patent 11,790,211, 2023
2023
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