Joshua V. Dillon
Joshua V. Dillon
Verified email at google.com
TitleCited byYear
Deep variational information bottleneck
AA Alemi, I Fischer, JV Dillon, K Murphy
arXiv preprint arXiv:1612.00410, 2016
2232016
Fixing a broken ELBO
AA Alemi, B Poole, I Fischer, JV Dillon, RA Saurous, K Murphy
arXiv preprint arXiv:1711.00464, 2017
133*2017
The locally weighted bag of words framework for document representation
G Lebanon, Y Mao, J Dillon
Journal of Machine Learning Research 8 (Oct), 2405-2441, 2007
722007
Tensorflow distributions
JV Dillon, I Langmore, D Tran, E Brevdo, S Vasudevan, D Moore, B Patton, ...
arXiv preprint arXiv:1711.10604, 2017
472017
Sequential document visualization
Y Mao, J Dillon, G Lebanon
IEEE transactions on visualization and computer graphics 13 (6), 1208-1215, 2007
432007
A unified optimization framework for robust pseudo-relevance feedback algorithms
JV Dillon, K Collins-Thompson
Proceedings of the 19th ACM international conference on Information and …, 2010
272010
Statistical translation, heat kernels and expected distances
J Dillon, Y Mao, G Lebanon, J Zhang
arXiv preprint arXiv:1206.5248, 2012
252012
Stochastic composite likelihood
JV Dillon, G Lebanon
Journal of Machine Learning Research 11 (Oct), 2597-2633, 2010
252010
Asymptotic analysis of generative semi-supervised learning
JV Dillon, K Balasubramanian, G Lebanon
arXiv preprint arXiv:1003.0024, 2010
162010
Uncertainty in the variational information bottleneck
AA Alemi, I Fischer, JV Dillon
arXiv preprint arXiv:1807.00906, 2018
152018
Statistical and computational tradeoffs in stochastic composite likelihood
J Dillon, G Lebanon
Artificial Intelligence and Statistics, 129-136, 2009
152009
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Y Ovadia, E Fertig, J Ren, Z Nado, D Sculley, S Nowozin, JV Dillon, ...
arXiv preprint arXiv:1906.02530, 2019
52019
Deep variational information bottleneck. arXiv 2017
AA Alemi, I Fischer, JV Dillon, K Murphy
arXiv preprint arXiv:1612.00410, 0
5
Likelihood Ratios for Out-of-Distribution Detection
J Ren, PJ Liu, E Fertig, J Snoek, R Poplin, MA DePristo, JV Dillon, ...
arXiv preprint arXiv:1906.02845, 2019
42019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport
M Hoffman, P Sountsov, JV Dillon, I Langmore, D Tran, S Vasudevan
arXiv preprint arXiv:1903.03704, 2019
32019
Quadrature Compound: An approximating family of distributions
J Dillon, I Langmore
Arxiv, 2018
12018
Tensorflow distributions
A Alemi, B Patton, D Moore, D Tran, E Brevdo, I Langmore, J Dillon, ...
12017
The TensorFlow Distributions Library
B Patton, D Moore, D Tran, E Brevdo, I Langmore, J Dillon, M Hoffman, ...
12017
Cumulative Revision Map
S Kim, JV Dillon, G Lebanon
arXiv preprint arXiv:1205.3205, 2012
12012
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport
D Tran, I Langmore, J Dillon, MD Hoffman, P Sountsov, S Vasudevan
2019
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Articles 1–20