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Causal Entropy Optimization


Aug 23, 2022
Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas

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Towards Computing an Optimal Abstraction for Structural Causal Models


Aug 01, 2022
Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas

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* 6 pages, 5 pages appendix, 2 figures Submitted to Causal Representation Learning workshop at the 38th Conference on Uncertainty in Artificial Intelligence (UAI CRL 2022) 

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Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap


Feb 23, 2022
Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol

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* Accepted for publication (with an oral presentation) at AISTATS 2022. A preliminary version of this paper was accepted in the NeurIPS 2021 workshop "Your Model is Wrong: Robustness and misspecification in probabilistic modeling". v2: added some references 

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Uncertainty-aware deep learning methods for robust diabetic retinopathy classification


Feb 02, 2022
Joel Jaskari, Jaakko Sahlsten, Theodoros Damoulas, Jeremias Knoblauch, Simo Särkkä, Leo Kärkkäinen, Kustaa Hietala, Kimmo Kaski

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Spatio-Temporal Variational Gaussian Processes


Nov 02, 2021
Oliver Hamelijnck, William J. Wilkinson, Niki A. Loppi, Arno Solin, Theodoros Damoulas

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Dynamic Causal Bayesian Optimization


Oct 26, 2021
Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas

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Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes


Sep 29, 2021
Cristopher Salvi, Maud Lemercier, Chong Liu, Blanka Hovarth, Theodoros Damoulas, Terry Lyons

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* Published at NeurIPS 2021 

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