Eric Nalisnick
Eric Nalisnick
Assistant Professor, University of Amsterdam
uci.edu의 이메일 확인됨 - 홈페이지
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Do deep generative models know what they don't know?
E Nalisnick, A Matsukawa, YW Teh, D Gorur, B Lakshminarayanan
arXiv preprint arXiv:1810.09136, 2018
2462018
Normalizing flows for probabilistic modeling and inference
G Papamakarios, E Nalisnick, DJ Rezende, S Mohamed, ...
Journal of Machine Learning Research 22 (57), 1-64, 2021
2222021
Improving document ranking with dual word embeddings
E Nalisnick, B Mitra, N Craswell, R Caruana
Proceedings of the 25th International Conference Companion on World Wide Web …, 2016
1652016
A dual embedding space model for document ranking
B Mitra, E Nalisnick, N Craswell, R Caruana
arXiv preprint arXiv:1602.01137, 2016
1242016
Stick-breaking variational autoencoders
E Nalisnick, P Smyth
arXiv preprint arXiv:1605.06197, 2016
120*2016
Approximate inference for deep latent gaussian mixtures
E Nalisnick, L Hertel, P Smyth
NIPS Workshop on Bayesian Deep Learning 2, 131, 2016
642016
Detecting out-of-distribution inputs to deep generative models using a test for typicality
E Nalisnick, A Matsukawa, YW Teh, B Lakshminarayanan
arXiv preprint arXiv:1906.02994 5, 5, 2019
572019
Character-to-character sentiment analysis in Shakespeare’s plays
ET Nalisnick, HS Baird
Proceedings of the 51st Annual Meeting of the Association for Computational …, 2013
542013
Hybrid models with deep and invertible features
E Nalisnick, A Matsukawa, YW Teh, D Gorur, B Lakshminarayanan
International Conference on Machine Learning, 4723-4732, 2019
392019
Extracting sentiment networks from Shakespeare's plays
ET Nalisnick, HS Baird
2013 12th International Conference on Document Analysis and Recognition, 758-762, 2013
362013
Bayesian batch active learning as sparse subset approximation
R Pinsler, J Gordon, E Nalisnick, JM Hernández-Lobato
arXiv preprint arXiv:1908.02144, 2019
352019
Dropout as a structured shrinkage prior
E Nalisnick, JM Hernández-Lobato, P Smyth
International Conference on Machine Learning, 4712-4722, 2019
172019
A scale mixture perspective of multiplicative noise in neural networks
E Nalisnick, A Anandkumar, P Smyth
arXiv preprint arXiv:1506.03208, 2015
17*2015
Infinite dimensional word embeddings
E Nalisnick, S Ravi
15*2017
On priors for bayesian neural networks
ET Nalisnick
UC Irvine, 2018
122018
Learning priors for invariance
E Nalisnick, P Smyth
International Conference on Artificial Intelligence and Statistics, 366-375, 2018
102018
Analyzing NIH funding patterns over time with statistical text analysis
J Park, M Blume-Kohout, R Krestel, E Nalisnick, P Smyth
Workshops at the Thirtieth AAAI Conference on Artificial Intelligence, 2016
62016
Expressive yet Tractable Bayesian Deep Learning via Subnetwork Inference
E Daxberger, E Nalisnick, JU Allingham, J Antorán, ...
arXiv preprint arXiv:2010.14689, 2020
52020
Learning approximately objective priors
E Nalisnick, P Smyth
arXiv preprint arXiv:1704.01168, 2017
52017
Predictive Complexity Priors
E Nalisnick, J Gordon, JM Hernández-Lobato
International Conference on Artificial Intelligence and Statistics, 694-702, 2021
32021
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