News | Javier Antorán

2023

I will be returning to CBL as a Research Fellow in January.

I will be returning to Google Research as a research intern in the Cerebra team in September!
I will be speaking at Generative models and uncertainty quantification in Copenhagen, September 20-21, 2023

I will be at ICML 2023 next week and at the 5th Symposium on Advances in Approximate Bayesian Inference (AABI 2023) which will be co-located with ICML in Honolulu Hawaii, on Sunday July 23rd, 2023. I will be presenting the papers
The I Cant Believe Its Not Better movement’s 2023 workshop proposal, for which I acted as an advisor, has been accepted to NeurIPS.

I am co-organising the 5th Symposium on Advances in Approximate Bayesian Inference (AABI 2023) which will be co-located with ICML in Honolulu Hawaii, on Sunday July 23rd, 2023.
I am back in Cambridge writing my PhD thesis and working on an exciting new project.

I joined Google Zurich as a Research Intern in the Cerebra team. I am working on source localisation and waveform synthesis, at the intersection of signal processing machine learning.

I will be speaking about Bayesian reasoning and giving a practical session on Bayesian Neural networks at the Deep Learning Indaba in Tunis from the 21st to 26th of August. All prac materials are publicly available here. The notebook for the Bayesian Deep Learning prac is here:

I will be attending ICML 2022 in Baltimore USA. I will be preseting my papers Adapting the Linearised Laplace Model Evidence for Modern Deep Learning and Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior. I will also be chairing the session on probabilistic methods and variational inference.
Our workshop on Understanding Deep Learning through Empirical Falsification has been accepted to NeurIPS2022. This workshop is part of the I Cant Believe Its Not Better movement.

I will be joining the Amsterdam Machine Learning Lab visiting Max Welling and Eric Nalisnick.

After an amazing year in Cambridge, I have joined the Machine Learning Group withing the Computational and Biological Learning Lab to pursue a PhD under the supervision of Professor José-Miguel Hernández-Lobato.

Together with Stratis Markou, I have released a library that implements most popular Bayesian Deep Learning methods: github.com/JavierAntoran/Bayesian-Neural-Networks

I have started the MPhil in Machine Learning and Machine Intelligence at the University of Cambridge.

I will be spending the summer at CERN developing telecommunications infrastructure for the ATLAS experiment.