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1WS 18/19 | Informatik 2
Probabilistic Programming Course
4 years ago by @kirk86
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2Graduate Summer School: Intelligent Extraction of Information from Graphs and High Dimensional Data (Schedule) - IPAM
Graduate Summer School: Intelligent Extraction of Information from Graphs and High Dimensional Data (Schedule) - IPAM
5 years ago by @kirk86
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2CS 3710: Advanced Topics in Artificial Intelligence (ISSP 3565) - Probabilistic Graphical Models
Probabilistic Graphical Models
5 years ago by @kirk86
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1Probabilistic Unsupervised Learning NIPS Tutorial
Probabilistic Unsupervised Learning NIPS Tutorial
5 years ago by @kirk86
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1Probabilistic Deep Learning MLSS2019-Madrid
Probabilistic Deep Learning
5 years ago by @kirk86
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1Probabilistic Models RAAIS2018
Probabilistic Models
5 years ago by @kirk86
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1Probabilistic Models DALI2018 keynote
Probabilistic Models
5 years ago by @kirk86
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1Probabilistic Machine Learning 4f13 Michaelmas 2018
Probabilistic Machine Learning 2018 Course @ Cambridge
5 years ago by @kirk86
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1CSE 515 - Statistical Methods in Computer Science - Spring 2009
Statistical Methods in Computer Science - Spring 2009
5 years ago by @kirk86
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1Handbook of Graphical Models
Handbook of Graphical Models by Statisticians
5 years ago by @kirk86
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1NLP Probabilistic Tutorial
Bayesian Probabilistic NLP Tutorial
5 years ago by @kirk86
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1Graphical Model Course 2014
Graphical Models Course CMU 2014
5 years ago by @kirk86
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1Martin Haugh's Web Page
Good Resources About Courses on Bayesian Methods and MCMC
5 years ago by @kirk86
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1Bayesian Non-Parametric Models at nips09npb.pdf
Bayesian Non-Parametric Models at NIPS 2009
5 years ago by @kirk86
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1EP roadmap
Expectation Propagation Techniques for Bayesian Inference
5 years ago by @kirk86
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1Machine Learning Summer School 2009
Bayesian Machine Learning Summer School 200
5 years ago by @kirk86
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1Microsoft PowerPoint - ProbabilisticProgramming_MLSS2009.ppt [Read-Only] [Compatibility Mode]
Probabilistic Programming Graphical Notation
5 years ago by @kirk86
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1One-shot learning with hierarchical non-parametric Bayesian
One-shot learning with hierarchical non-parametric Bayesian
5 years ago by @kirk86
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1MP4/P4 Statistical Physics
Statistical Physics Lecture Notes
5 years ago by @kirk86
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1NIPS 2014 Workshop on Advances in Variational Inference
NIPS 2014 Workshop on Advances in Variational Inference
5 years ago by @kirk86
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1A Bayesian analysis concludes beyond a reasonable doubt that SARS-CoV-2 is not a natural zoonosis but instead is laboratory derived
S. Quay. (Mar 29, 2021)
3 years ago by @3lli3
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1Finite mixture models are typically inconsistent for the number of components
D. Cai, T. Campbell, and T. Broderick. (2020)cite arxiv:2007.04470Comment: 16 pages, 1 figure.
4 years ago by @kirk86
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3SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models
Y. Luo, A. Beatson, M. Norouzi, J. Zhu, D. Duvenaud, R. Adams, and R. Chen. International Conference on Learning Representations, (2020)
5 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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1Learning deep kernels for exponential family densities
L. Wenliang, D. Sutherland, H. Strathmann, and A. Gretton. (2018)cite arxiv:1811.08357.
5 years ago by @kirk86
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2An Axiomatic Utility Theory for Dempster-Shafer Belief Functions
T. Denoeux, and P. Shenoy. (2019)
5 years ago by @kirk86
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2Interpreting, Axiomatising and Representing Coherent Choice Functions in Terms of Desirability
J. De Bock, and G. de Cooman. Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications, volume 103 of Proceedings of Machine Learning Research, page 125--134. Thagaste, Ghent, Belgium, PMLR, (03--06 Jul 2019)
5 years ago by @kirk86
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3Imprecise Probabilities as a Semantics for Intuitive Probabilistic Reasoning
H. Crane. (2019)
5 years ago by @kirk86
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1A tutorial on Dirichlet process mixture modeling
Y. Li, E. Schofield, and M. Gönen. Journal of Mathematical Psychology, (2019)
5 years ago by @kirk86
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1Improved Central Limit Theorem and bootstrap approximations in high dimensions
V. Chernozhukov, D. Chetverikov, K. Kato, and Y. Koike. (2019)cite arxiv:1912.10529Comment: 53 pages.
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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2Neural Tangents: Fast and Easy Infinite Neural Networks in Python
R. Novak, L. Xiao, J. Hron, J. Lee, A. Alemi, J. Sohl-Dickstein, and S. Schoenholz. (2019)cite arxiv:1912.02803.
5 years ago by @kirk86
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2Soft robust solutions to possibilistic optimization problems
A. Kasperski, and P. Zielinski. (2019)cite arxiv:1912.01516.
5 years ago by @kirk86
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2Derivative-Free Estimation of the Score Vector and Observed Information Matrix with Application to State-Space Models
A. Doucet, P. Jacob, and S. Rubenthaler. (2013)cite arxiv:1304.5768Comment: Technical report, 43 pages, 7 figures.
5 years ago by @kirk86
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1Graphical models, exponential families, and variational inference - compressed
M. Wainwright, and M. Jordan. (2008)
5 years ago by @kirk86
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1Smart Regularization of Deep Architectures
C. Louizos. (2015)
5 years ago by @kirk86
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2Towards Bayesian Deep Learning: A Framework and Some Existing Methods
H. Wang, and D. Yeung. IEEE Transactions on Knowledge and Data Engineering, 28 (12): 3395-3408 (December 2016)
5 years ago by @kirk86
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12Graphical Models, Exponential Families, and Variational Inference
M. Wainwright, and M. Jordan. (2008)
5 years ago by @kirk86
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1Multiple Futures Prediction
C. Tang, and R. Salakhutdinov. (2019)
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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