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1Deep Generative Models Tutorial
Deep Generative Models Tutorial
5 years ago by @kirk86
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3When are Non-Parametric Methods Robust?
R. Bhattacharjee, and K. Chaudhuri. (2020)cite arxiv:2003.06121Comment: under review for ICML 2020.
4 years ago by @kirk86
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2Subadditivity of Probability Divergences on Bayes-Nets with Applications to Time Series GANs
M. Ding, C. Daskalakis, and S. Feizi. (2020)cite arxiv:2003.00652.
5 years ago by @kirk86
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2Cutting out the Middle-Man: Training and Evaluating Energy-Based Models without Sampling
W. Grathwohl, K. Wang, J. Jacobsen, D. Duvenaud, and R. Zemel. (2020)cite arxiv:2002.05616.
5 years ago by @kirk86
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3Input Complexity and Out-of-distribution Detection with Likelihood-based Generative Models
J. Serrà, D. Álvarez, V. Gómez, O. Slizovskaia, J. Núñez, and J. Luque. International Conference on Learning Representations, (2020)
5 years ago by @kirk86
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1Predictive Coding, Variational Autoencoders, and Biological Connections
J. Marino. (2019)
5 years ago by @kirk86
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2Input complexity and out-of-distribution detection with likelihood-based generative models
J. Serrà, D. Álvarez, V. Gómez, O. Slizovskaia, J. Núñez, and J. Luque. (2019)cite arxiv:1909.11480Comment: Includes appendix.
5 years ago by @kirk86
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2Multivariate Triangular Quantile Maps for Novelty Detection
J. Wang, S. Sun, and Y. Yu. page 5061-5072. (2019)
5 years ago by @kirk86
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3Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
W. Grathwohl, K. Wang, J. Jacobsen, D. Duvenaud, M. Norouzi, and K. Swersky. (2019)cite arxiv:1912.03263.
5 years ago by @kirk86
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1Density estimation using Real NVP
L. Dinh, J. Sohl-Dickstein, and S. Bengio. (2016)cite arxiv:1605.08803Comment: 10 pages of main content, 3 pages of bibliography, 18 pages of appendix. Accepted at ICLR 2017.
5 years ago by @kirk86
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1Unifying generative models and exact likelihood-free inference with conditional bijections
K. Cranmer, and G. Louppe. (2016)
5 years ago by @kirk86
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2Input complexity and out-of-distribution detection with likelihood-based generative models
J. Serrà, D. Álvarez, V. Gómez, O. Slizovskaia, J. Núñez, and J. Luque. (2019)cite arxiv:1909.11480Comment: Includes appendix.
5 years ago by @kirk86
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2Normalizing Flows for Probabilistic Modeling and Inference
G. Papamakarios, E. Nalisnick, D. Rezende, S. Mohamed, and B. Lakshminarayanan. (2019)cite arxiv:1912.02762Comment: Review article. 60 pages, 4 figures.
5 years ago by @kirk86
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1Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control
S. Kamthe, and M. Deisenroth. (2017)cite arxiv:1706.06491Comment: Accepted at AISTATS 2018,.
5 years ago by @kirk86
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1Pathologies of Factorised Gaussian and MC Dropout Posteriors in Bayesian Neural Networks
A. Foong, D. Burt, Y. Li, and R. Turner. (2019)cite arxiv:1909.00719.
5 years ago by @kirk86
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2Diverse Image Synthesis from Semantic Layouts via Conditional IMLE
K. Li, T. Zhang, and J. Malik. (2018)cite arxiv:1811.12373Comment: 18 pages, 16 figures; IEEE International Conference on Computer Vision (ICCV), 2019.
5 years ago by @kirk86
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2Uncertainty-Aware Learning from Demonstration using Mixture Density Networks with Sampling-Free Variance Modeling
S. Choi, K. Lee, S. Lim, and S. Oh. (2017)cite arxiv:1709.02249.
5 years ago by @kirk86
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1DEEP MIXTURE DENSITY NETWORK FOR STATISTICAL MODEL-BASED FEATURE ENHANCEMEN
K. Kinoshita, M. Delcroix, A. Ogawa, T. Higuehi, and T. Nakatani. (2017)
5 years ago by @kirk86
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1Deep Generative Models Tutorial

publications (hide)17
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3When are Non-Parametric Methods Robust?

2Subadditivity of Probability Divergences on Bayes-Nets with Applications to Time Series GANs

2Cutting out the Middle-Man: Training and Evaluating Energy-Based Models without Sampling

3Input Complexity and Out-of-distribution Detection with Likelihood-based Generative Models

1Predictive Coding, Variational Autoencoders, and Biological Connections

2Input complexity and out-of-distribution detection with likelihood-based generative models

2Multivariate Triangular Quantile Maps for Novelty Detection

3Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One

1Density estimation using Real NVP

1Unifying generative models and exact likelihood-free inference with conditional bijections

2Input complexity and out-of-distribution detection with likelihood-based generative models

2Normalizing Flows for Probabilistic Modeling and Inference

1Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control

1Pathologies of Factorised Gaussian and MC Dropout Posteriors in Bayesian Neural Networks

2Diverse Image Synthesis from Semantic Layouts via Conditional IMLE

2Uncertainty-Aware Learning from Demonstration using Mixture Density Networks with Sampling-Free Variance Modeling

1DEEP MIXTURE DENSITY NETWORK FOR STATISTICAL MODEL-BASED FEATURE ENHANCEMEN

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