Παρακολούθηση
Javier Antoran
Javier Antoran
University of Cambridge
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα cam.ac.uk - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty
U Bhatt, J Antorán, Y Zhang, QV Liao, P Sattigeri, R Fogliato, ...
2021 AAAI/ACM Conference on AI, Ethics, and Society, 2020
2692020
Getting a CLUE: A Method for Explaining Uncertainty Estimates
J Antorán, U Bhatt, T Adel, A Weller, JM Hernández-Lobato
International Conference on Learning Representations (ICLR), 2021, 2020
1332020
Depth uncertainty in neural networks
J Antorán, JU Allingham, JM Hernández-Lobato
Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020
1242020
Bayesian Deep Learning via Subnetwork Inference
E Daxberger, E Nalisnick, JU Allingham, J Antorán, ...
International Conference on Machine Learning, 2021, 2020
1012020
Deep end-to-end causal inference
T Geffner, J Antoran, A Foster, W Gong, C Ma, E Kiciman, A Sharma, ...
arXiv preprint arXiv:2202.02195, 2022
802022
Adapting the linearised laplace model evidence for modern deep learning
J Antorán, D Janz, JU Allingham, E Daxberger, RR Barbano, E Nalisnick, ...
International Conference on Machine Learning, 796-821, 2022
292022
Sampling-based inference for large linear models, with application to linearised Laplace
J Antorán, S Padhy, R Barbano, E Nalisnick, D Janz, ...
arXiv preprint arXiv:2210.04994, 2022
192022
Sampling from Gaussian process posteriors using stochastic gradient descent
JA Lin, J Antorán, S Padhy, D Janz, JM Hernández-Lobato, A Terenin
Advances in Neural Information Processing Systems 36, 36886-36912, 2023
172023
SE (3) equivariant augmented coupling flows
L Midgley, V Stimper, J Antorán, E Mathieu, B Schölkopf, ...
Advances in Neural Information Processing Systems 36, 2024
162024
Disentangling and learning robust representations with natural clustering
J Antoran, A Miguel
2019 18th IEEE International Conference On Machine Learning And Applications …, 2019
162019
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior
J Antorán, R Barbano, J Leuschner, JM Hernández-Lobato, B Jin
arXiv preprint arXiv:2203.00479, 2022
15*2022
Expressive yet tractable Bayesian deep learning via subnetwork inference
E Daxberger, E Nalisnick, J Allingham, J Antorán, JM Hernández-Lobato
152020
Linearised laplace inference in networks with normalisation layers and the neural g-prior
J Antorán, JU Allingham, D Janz, E Daxberger, E Nalisnick, ...
Fourth Symposium on Advances in Approximate Bayesian Inference, 2022
102022
Bayesian experimental design for computed tomography with the linearised deep image prior
R Barbano, J Leuschner, J Antorán, B Jin, JM Hernández-Lobato
Adaptive Experimental Design and Active Learning workshop at ICML 2022, 2022
82022
& Xiang, A.(2021, July). Uncertainty as a form of transparency: Measuring, communicating, and using uncertainty
U Bhatt, J Antorán, Y Zhang, QV Liao, P Sattigeri, R Fogliato
Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 401-413, 0
8
Understanding Uncertainty in Bayesian Neural Networks
JA Cabiscol
72019
Variational depth search in ResNets
J Antorán, JU Allingham, JM Hernández-Lobato
arXiv preprint arXiv:2002.02797, 2020
62020
Stochastic Gradient Descent for Gaussian Processes Done Right
JA Lin, S Padhy, J Antorán, A Tripp, A Terenin, C Szepesvári, ...
arXiv preprint arXiv:2310.20581, 2023
52023
A probabilistic deep image prior over image space
R Barbano, J Antorán, JM Hernández-Lobato, B Jin
Fourth Symposium on Advances in Approximate Bayesian Inference, 2022
42022
Online laplace model selection revisited
JA Lin, J Antorán, JM Hernández-Lobato
arXiv preprint arXiv:2307.06093, 2023
32023
Δεν είναι δυνατή η εκτέλεση της ενέργειας από το σύστημα αυτή τη στιγμή. Προσπαθήστε ξανά αργότερα.
Άρθρα 1–20