Talks

My most recent talks, together with slides, are found below.

2023

Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent Research Talk at the Cambridge University Engineering Department, UK
[Slides]

The Linearised Laplace Approximation Machine Learning Reading Group Talk at the Cambridge University Engineering Department, UK
[Link], [Slides]

2022

Bayesian Inference
Talk at the 2022 Deep Learning indaba in Tunis [Link], [Slides]

Adapting the Linearised Laplace Model Evidence for Modern Deep Learning
Spotlight talk at ICML 2022 in Baltimore, USA [Slides], [Video]

Developments in Inference with Linearised Neural Networks
Mathematics of Deep Learning Reading Group at the Centre for Mathematical Sciences, University of Cambridge
[Slides]

Bayesian Deep Learning with Linearised Neural Networks
Talk at the Alto University and ELLIS unit Helsinki Seminar on Advances in Probabilistic Machine Learning
[Link], [Slides]

Linearised Laplace Inference in Networks with Normalisation Layers and the Neural g-Prior
Contributed talk at 4th Symposium on Advances in Approximate Bayesian Inference (AABI)
[Link], [Slides]

2021

An Introduction to PAC-Bayes
Machine Learning Reading Group Talk at the Cambridge University Engineering Department, UK
[Link], [Slides]

Tractable Bayesian Deep Learning on Subnetworks
Seminar at the UCL Centre for Inverse Problems in Imaging
[Link], [Slides]

Getting a CLUE: A Method for Explaining Uncertainty Estimates (CCAIM Showcase)
Research showcase talk at the Cambridge Center for AI in Medicine (CCAIM)
[Link], [Slides]

Inference in Stochastic Processes
Machine Learning Reading Group Talk at the Cambridge University Engineering Department, UK
[Link], [Slides]

2020

Depth Uncertainty in Neural Networks (AMLAB Edition)
Talk in the Amsterdam Machine Learning Group (AMLAB)’s weekly seminar
[Link], [Slides]

ML Interpretability: Beyond Feature Importance
Talk for RSQRD-AI’s session on Explainable AI
[Link], [Slides]

Depth Uncertainty in Neural Networks
Spotlight presentation at the Uncertainty & Robustness in Deep Learning (UDL) workshop at ICML 2020
[Link], [Slides]

Getting a CLUE: A Method for Explaining Uncertainty Estimates
Oral presentation at the Machine Learning in Real Life (ML-IRL) workshop at ICLR 2020
[Link], [Slides]

Variational Depth Search in ResNets
Oral presentation at the Neural Architecture Search (NAS) workshop at ICLR 2020
[Link], [Slides]

Self-Supervised Representation Learning
Machine Learning Reading Group Talk at the Cambridge University Engineering Department, UK
[Link], [Slides]

2019

Disentangling in Variational Autoencoders with Natural Clustering
Oral presentation at the 18th IEEE International Conference on Machine Learning and Applications - ICMLA 2019, Boca Raton, Florida, USA
[Slides]

Bayesian Methods in Deep Learning
Research Seminar at the Computer Engineering Department at the University of Zaragoza, Spain.
[Link], [Slides]