# About

I am a PhD student in Machine Learning at the University of Cambridge under the supervision of Dr. José Miguel Hernández-Lobato. I’m interested in Bayesian deep learning, representation learning, uncertainty in machine learning and information theory. I graduated from the University of Zaragoza in 2018 with an honorary distinction (“premio extraordinario”) in Telecommunications Engineering (EE/CS). I was awarded an MPhil in Machine Learning with distinction by the University of Cambridge in 2019. I also do freelance engineering consulting and am a co-founder of arisetech.es. Bellow are links to some of my recent work.

## 2020

**Bayesian Deep Learning via Subnetwork Inference**

E. Daxberger, E. Nalisnick, J. U. Allingham, **J. Antorán** and J. M. Hernández-Lobato.

*38th International Conference on Machine Learning (ICML)*, 2021.

[Paper], [Poster]

**Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty**

U. B., **J. Antorán**, Y. Z., Q. V. L., P. S., R. F., G. G. M., R. K., J. S., O. T., L. N., R. C., A. W. and A. X.

*4th AAAI / ACM conference on Artificial Intelligence, Ethics, and Society (AIES)*, 2021.

[Paper]

**Depth Uncertainty in Neural Networks**

**J. Antorán**, J. U. Allingham and J. M. Hernández-Lobato.

*34th Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada.* 2020.

[Paper], [Poster], [bibtex], [code]

**Getting a CLUE: A Method for Explaining Uncertainty Estimates**

**J. Antorán**, U. Bhatt, T. Adel, A. Weller and J. M. Hernández-Lobato.

*Oral presentation at The Ninth International Conference on Learning Representations (ICLR)*, 2021.

[Paper], [Poster], [bibtex], [code]

**Variational Depth Search in ResNets**

**J. Antorán**, J. U. Allingham and J. M. Hernández-Lobato.

*Contributed talk at 1st Workshop on Neural Architecture Search at ICLR* 2020.

[Paper], [Poster], [bibtex], [code]

## 2019

**Understanding Uncertainty in Bayesian Neural Networks**

**J. Antorán**

*MPhil Thesis (Awarded Distinction)*

[Thesis], [bibtex], [Poster]

**Uncertainty in Bayesian Neural Networks (github repo)**

**J. Antorán** and E. Markou.

*Presented poster at the Workshop on The Mathematics of Deep Learning and Data Science, The Isaac Newton Institute for Mathematical Sciences, Cambridge, UK.* 2019.

[Poster], [Code]

## 2018

**Disentangling in Variational Autoencoders with Natural Clustering**

**J. Antorán** and A. Miguel.

*Successfully defended Bachelor’s Thesis at the University of Zaragoza (9.8/10, Honorary Distinction).*

*Accepted as an oral presentation at the 18th IEEE International Conference on Machine Learning and Applications - ICMLA 2019, Boca Raton, Florida, USA.* 2019.

[Paper], [bibtex], [Thesis (Spanish)]

**FELIX DAQ Integration Test Tool for the ATLAS experiment at CERN.**

**J. Antorán** and J. Schumacher.

*Work done during a Summer studentship at CERN.*

[Technical Report], [bibtex]