Invited Talks
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Reinforcement Learning at Spotify: An example with Interactive Radio (2022)
Deep Learning Summit, London, UK -
Scalability of Gaussian Processes (2022)
GPSS 2022, Sheffield, UK
[slides] -
Scalability of Gaussian Processes (2021)
GPSS 2021, online
[slides] -
Variational Gaussian Processes (2020)
GPSS 2020, online
[slides] -
Scaling up Gaussian processes for real-world data (2020)
Gaussian Processes Cambridge Meetup, Cambridge, UK
[slides] -
Bayesian Optimization: Basics & Challenges (2020)
Boston Machine Learning Meetup, Boston, MA, US
[slides] -
What uncertainty do we get? (2019)
Workshop on Uncertainty Propagation in Composite Models, Munich, Germany
[slides] -
Scalable Gaussian Processes (2019)
GPSS 2019, Sheffield, UK
[slides] -
Scalable Gaussian Processes (2018)
GPSS 2018, Sheffield, UK
[slides] -
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes (2017)
Gaussian Process Approximation Workshop 2017, Berlin, Germany
[slides] -
Preferential Bayesian Optmization (2017)
ICML 2017, Sydney, Australia
[video] [slides] -
Scaling Up Deep Gaussian Processes (2016)
Deep Probabilistic Model Meeting, London, UK.
[slides] -
Variational Auto-Encoded Deep Gaussian Processes (2015)
Alan Turing Institute Deep Learning Scoping Workshop, Edinburgh, UK. -
Probabilistic Unsupervised Learning with Latent Variable Models (2015)
Cluster of Excellence Hearing4all and Dept for Medical Physics and Acoustics, Carl von Ossietzky University Oldenburg, Germany. -
Unsupervised Learning with Latent Variable Models (2015)
Computational and Biological Learning Lab, University of Cambridge, UK. -
Variational Hierarchical Communities of Experts (2015)
CSML lunch seminar, UCL, UK.
[slides] -
Spike and Slab GPLVM for Extracting Regulator Activity Profiles (2015)
RADIANT meeting, Zurich, Switzerland. -
Spike and Slab GPLVM for Gene Express Analysis (2014)
Faculty of Life Sciences, University of Manchester, UK. -
Speeding Up Bayesian GP-LVM with Parallelization and GPU accelerations (2014)
RADIANT meeting, Heidelberg, Germany -
What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach (2013)
Redwood Center for Theoretical Neuroscience, UC Berkeley, US -
Unsupervised Learning of Invariant Object Representations – A Probabilistic Generative Modeling Approach (2013)
LEAR, Grenoble, France -
Autonomous Cleaning of Corrupted Scanned Documents – A Generative Modeling Approach (2012)
oral presentation, Computer Vision and Pattern Recognition (CVPR) 2012, Providence, Rhode Island, US