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Stochastic Aggregation in Graph Neural Networks


Feb 26, 2021
Yuanqing Wang, Theofanis Karaletsos


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Variational Auto-Regressive Gaussian Processes for Continual Learning


Jun 09, 2020
Sanyam Kapoor, Theofanis Karaletsos, Thang D. Bui

* Preprint. Under review 

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Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights


Feb 10, 2020
Theofanis Karaletsos, Thang D. Bui

* 12 pages main paper, 13 pages appendix 

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Generalized Hidden Parameter MDPs Transferable Model-based RL in a Handful of Trials


Feb 08, 2020
Christian F. Perez, Felipe Petroski Such, Theofanis Karaletsos

* paper presented at AAAI 2020 as oral presentation, 9 pages 

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Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference


Jan 17, 2019
Xinyu Hu, Paul Szerlip, Theofanis Karaletsos, Rohit Singh

* Third workshop on Bayesian Deep Learning (NeurIPS 2018) 

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Efficient transfer learning and online adaptation with latent variable models for continuous control


Dec 08, 2018
Christian F. Perez, Felipe Petroski Such, Theofanis Karaletsos

* Presented at Continual Learning Workshop, NeurIPS 2018, Montreal, Canada. 5 pages, 4 figures 

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Pyro: Deep Universal Probabilistic Programming


Oct 18, 2018
Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul Szerlip, Paul Horsfall, Noah D. Goodman

* Submitted to JMLR MLOSS track 

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Probabilistic Meta-Representations Of Neural Networks


Oct 01, 2018
Theofanis Karaletsos, Peter Dayan, Zoubin Ghahramani

* presented at UAI 2018 Uncertainty In Deep Learning Workshop (UDL AUG. 2018) 

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Pathwise Derivatives for Multivariate Distributions


Jun 05, 2018
Martin Jankowiak, Theofanis Karaletsos


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Likelihood-free inference with emulator networks


May 23, 2018
Jan-Matthis Lueckmann, Giacomo Bassetto, Theofanis Karaletsos, Jakob H. Macke


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Conditional Similarity Networks


Apr 10, 2017
Andreas Veit, Serge Belongie, Theofanis Karaletsos

* CVPR 2017 

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Adversarial Message Passing For Graphical Models


Dec 15, 2016
Theofanis Karaletsos

* (12 pages, 2 figures) Presented at NIPS Advances In Approximate Inference 2016 (AABI 2016) 

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Bayesian representation learning with oracle constraints


Mar 01, 2016
Theofanis Karaletsos, Serge Belongie, Gunnar Rätsch

* 16 pages, publishes in ICLR 16 

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Knowledge Transfer with Medical Language Embeddings


Feb 10, 2016
Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch

* 6 pages, 2 figures, to appear at SDM-DMMH 2016 

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A Generative Model of Words and Relationships from Multiple Sources


Dec 03, 2015
Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch

* 8 pages, 5 figures; incorporated feedback from reviewers; to appear in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence 2016 

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Automatic Relevance Determination For Deep Generative Models


Aug 26, 2015
Theofanis Karaletsos, Gunnar Rätsch

* equations 8-12 updated 

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