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Joshua V. Dillon
Joshua V. Dillon
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Title
Cited by
Cited by
Year
Deep variational information bottleneck
AA Alemi, I Fischer, JV Dillon, K Murphy
arXiv preprint arXiv:1612.00410, 2016
17472016
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, J Dillon, ...
Advances in neural information processing systems 32, 2019
16752019
Likelihood ratios for out-of-distribution detection
J Ren, PJ Liu, E Fertig, J Snoek, R Poplin, M Depristo, J Dillon, ...
Advances in neural information processing systems 32, 2019
7052019
Fixing a broken ELBO
A Alemi, B Poole, I Fischer, J Dillon, RA Saurous, K Murphy
International conference on machine learning, 159-168, 2018
6162018
Tensorflow distributions
JV Dillon, I Langmore, D Tran, E Brevdo, S Vasudevan, D Moore, B Patton, ...
arXiv preprint arXiv:1711.10604, 2017
6032017
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
1152019
Uncertainty in the variational information bottleneck
AA Alemi, I Fischer, JV Dillon
arXiv preprint arXiv:1807.00906, 2018
982018
The Locally Weighted Bag of Words Framework for Document Representation.
G Lebanon, Y Mao, J Dillon
Journal of Machine Learning Research 8 (10), 2007
962007
Density of states estimation for out of distribution detection
W Morningstar, C Ham, A Gallagher, B Lakshminarayanan, A Alemi, ...
International Conference on Artificial Intelligence and Statistics, 3232-3240, 2021
832021
Can you trust your model’s uncertainty
Y Ovadia, E Fertig, J Ren, Z Nado, D Sculley, S Nowozin, JV Dillon, ...
Evaluating predictive uncertainty under dataset shift, 2019
652019
The k-tied normal distribution: A compact parameterization of Gaussian mean field posteriors in Bayesian neural networks
J Swiatkowski, K Roth, B Veeling, L Tran, J Dillon, J Snoek, S Mandt, ...
International conference on machine learning, 9289-9299, 2020
602020
Sequential document visualization
Y Mao, J Dillon, G Lebanon
IEEE transactions on visualization and computer graphics 13 (6), 1208-1215, 2007
532007
Videopoet: A large language model for zero-shot video generation
D Kondratyuk, L Yu, X Gu, J Lezama, J Huang, R Hornung, H Adam, ...
arXiv preprint arXiv:2312.14125, 2023
522023
Hydra: Preserving ensemble diversity for model distillation
L Tran, BS Veeling, K Roth, J Swiatkowski, JV Dillon, J Snoek, S Mandt, ...
arXiv preprint arXiv:2001.04694, 2020
472020
tfp. mcmc: Modern Markov chain Monte Carlo tools built for modern hardware
J Lao, C Suter, I Langmore, C Chimisov, A Saxena, P Sountsov, D Moore, ...
arXiv preprint arXiv:2002.01184, 2020
392020
Deep variational information bottleneck. arXiv 2016
AA Alemi, I Fischer, JV Dillon, K Murphy
arXiv preprint arXiv:1612.00410, 0
36
Stochastic composite likelihood
JV Dillon, G Lebanon
The Journal of Machine Learning Research 11, 2597-2633, 2010
322010
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
292010
Statistical translation, heat kernels and expected distances
J Dillon, Y Mao, G Lebanon, J Zhang
arXiv preprint arXiv:1206.5248, 2012
262012
PACm-Bayes: Narrowing the empirical risk gap in the misspecified Bayesian regime
WR Morningstar, A Alemi, JV Dillon
International Conference on Artificial Intelligence and Statistics, 8270-8298, 2022
212022
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