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TyXe: Pyro-based Bayesian neural nets for Pytorch



Hippolyt Ritter , Theofanis Karaletsos

* Previously presented at PROBPROG 2020 

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Localized Uncertainty Attacks



Ousmane Amadou Dia , Theofanis Karaletsos , Caner Hazirbas , Cristian Canton Ferrer , Ilknur Kaynar Kabul , Erik Meijer

* CVPR 2021 Workshop on Adversarial Machine Learning in Computer Vision 

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Stochastic Aggregation in Graph Neural Networks



Yuanqing Wang , Theofanis Karaletsos


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Variational Auto-Regressive Gaussian Processes for Continual Learning



Sanyam Kapoor , Theofanis Karaletsos , Thang D. Bui

* Preprint. Under review 

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Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights



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



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



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



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



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



Theofanis Karaletsos , Peter Dayan , Zoubin Ghahramani

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

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