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2020 – today
- 2023
[i14]Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Zeljko Kereta, Bangti Jin:
Fast and Painless Image Reconstruction in Deep Image Prior Subspaces. CoRR abs/2302.10279 (2023)- 2022
- [c7]Javier Antorán, David Janz, James Urquhart Allingham, Erik A. Daxberger, Riccardo Barbano, Eric T. Nalisnick, José Miguel Hernández-Lobato:
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning. ICML 2022: 796-821 - [i13]Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang:
Deep End-to-end Causal Inference. CoRR abs/2202.02195 (2022) - [i12]Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin:
A Probabilistic Deep Image Prior for Computational Tomography. CoRR abs/2203.00479 (2022) - [i11]Javier Antorán, David Janz, James Urquhart Allingham, Erik A. Daxberger, Riccardo Barbano, Eric T. Nalisnick, José Miguel Hernández-Lobato:
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning. CoRR abs/2206.08900 (2022) - [i10]Riccardo Barbano, Johannes Leuschner, Javier Antorán, Bangti Jin, José Miguel Hernández-Lobato:
Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior. CoRR abs/2207.05714 (2022) - [i9]Javier Antorán, Shreyas Padhy, Riccardo Barbano, Eric T. Nalisnick, David Janz, José Miguel Hernández-Lobato:
Sampling-based inference for large linear models, with application to linearised Laplace. CoRR abs/2210.04994 (2022) - 2021
- [c6]Umang Bhatt, Javier Antorán, Yunfeng Zhang, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Madhulika Srikumar, Adrian Weller, Alice Xiang
:
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. AIES 2021: 401-413 - [c5]Chelsea Murray, James Urquhart Allingham, Javier Antorán, José Miguel Hernández-Lobato:
Addressing Bias in Active Learning with Depth Uncertainty Networks... or Not. ICBINB@NeurIPS 2021: 59-63 - [c4]Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández-Lobato:
Getting a CLUE: A Method for Explaining Uncertainty Estimates. ICLR 2021 - [c3]Erik A. Daxberger, Eric T. Nalisnick, James Urquhart Allingham, Javier Antorán, José Miguel Hernández-Lobato:
Bayesian Deep Learning via Subnetwork Inference. ICML 2021: 2510-2521 - [i8]Chelsea Murray, James Urquhart Allingham, Javier Antorán, José Miguel Hernández-Lobato:
Depth Uncertainty Networks for Active Learning. CoRR abs/2112.06796 (2021) - [i7]Chelsea Murray, James Urquhart Allingham, Javier Antorán, José Miguel Hernández-Lobato:
Addressing Bias in Active Learning with Depth Uncertainty Networks... or Not. CoRR abs/2112.06926 (2021) - 2020
- [c2]Javier Antorán, James Urquhart Allingham, José Miguel Hernández-Lobato:
Depth Uncertainty in Neural Networks. NeurIPS 2020 - [i6]Javier Antorán, James Urquhart Allingham, José Miguel Hernández-Lobato:
Variational Depth Search in ResNets. CoRR abs/2002.02797 (2020) - [i5]Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández-Lobato:
Getting a CLUE: A Method for Explaining Uncertainty Estimates. CoRR abs/2006.06848 (2020) - [i4]Javier Antorán, James Urquhart Allingham, José Miguel Hernández-Lobato:
Depth Uncertainty in Neural Networks. CoRR abs/2006.08437 (2020) - [i3]Erik A. Daxberger, Eric T. Nalisnick, James Urquhart Allingham, Javier Antorán, José Miguel Hernández-Lobato:
Expressive yet Tractable Bayesian Deep Learning via Subnetwork Inference. CoRR abs/2010.14689 (2020) - [i2]Umang Bhatt, Yunfeng Zhang, Javier Antorán, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Adrian Weller, Alice Xiang:
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. CoRR abs/2011.07586 (2020)
2010 – 2019
- 2019
- [c1]Javier Antorán, Antonio Miguel:
Disentangling and Learning Robust Representations with Natural Clustering. ICMLA 2019: 694-699 - [i1]Javier Antorán, Antonio Miguel:
Disentangling in Variational Autoencoders with Natural Clustering. CoRR abs/1901.09415 (2019)
Coauthor Index
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last updated on 2023-05-24 21:39 CEST by the dblp team
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