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Javier Antorn

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

7

Venues

4

Active years

2019–2024

Best venue rank

A*

Where they publish

Papers

7 indexed papers, newest first.

YearVenueTitleAuthors
2024ICLRStochastic Gradient Descent for Gaussian Processes Done Right.Jihao Andreas Lin, Shreyas Padhy, Javier Antorn, Austin Tripp, Alexander Terenin, Csaba Szepesvri, Jos Miguel Hernndez-Lobato, David Janz
2023ICLRSampling-based inference for large linear models, with application to linearised Laplace.Javier Antorn, Shreyas Padhy, Riccardo Barbano, Eric T. Nalisnick, David Janz, Jos Miguel Hernndez-Lobato
2022ICMLAdapting the Linearised Laplace Model Evidence for Modern Deep Learning.Javier Antorn, David Janz, James Urquhart Allingham, Erik A. Daxberger, Riccardo Barbano, Eric T. Nalisnick, Jos Miguel Hernndez-Lobato
2021AIESUncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.Umang Bhatt, Javier Antorn, Yunfeng Zhang, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melanon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Madhulika Srikumar, Adrian Weller, Alice Xiang
2021ICLRGetting a CLUE: A Method for Explaining Uncertainty Estimates.Javier Antorn, Umang Bhatt, Tameem Adel, Adrian Weller, Jos Miguel Hernndez-Lobato
2021ICMLBayesian Deep Learning via Subnetwork Inference.Erik A. Daxberger, Eric T. Nalisnick, James Urquhart Allingham, Javier Antorn, Jos Miguel Hernndez-Lobato
2019ICMLADisentangling and Learning Robust Representations with Natural Clustering.Javier Antorn, Antonio Miguel