Previously, I did a MRes Computational Statistics and Machine Learning at UCL with David Barber and a MSc in Computer Science at the University of Oxford with Yarin Gal. Prior to that I studied computer science at the University of Manchester for my undergraduate. At the time, I also had an one year industrial placement with Morgan Stanley, during which I worked with a global team to create tools for managing and monitoring the cloud platform that has a huge number of servers located around the world.
Just like lots of computer scientists, I have faith in technology. Even though technology won’t solve all the problems for you, I believe it will certainly take you closer to the answers.
At the moment, I am very interested in Machine Learning, a field that has amazing impacts on human life.
|Nov 3, 2023
|I was invited to give a talk at Imperial College London - CSML reading group!
|Nov 2, 2023
|Check out our new workshop paper “The SVHN Dataset Is Deceptive for Probabilistic Generative Models Due to a Distribution Mismatch” to know more about distribution mismatch in the SVHN dataset!
|Mar 13, 2023
|Check out our new blog post “Large Language Models Are Zero-Shot Problem Solvers — Just Like Modern Computers” to find out the interesting connection between LLMs and modern computers!
|Jan 20, 2023
|Our paper “Trading Information between Latents in Hierarchical Variational Autoencoders” has been accepted at ICLR!
|Jan 20, 2023
|Our paper “Iterative Teaching by Data Hallucination” has been accepted at AISTATS!
- A Compact Representation for Bayesian Neural Networks By Removing Permutation SymmetryarXiv preprint arXiv:2401.00611, 2023NeurIPS 2023 Workshop on Unifying Representations in Neural Models
- The SVHN Dataset Is Deceptive for Probabilistic Generative Models Due to a Distribution MismatcharXiv preprint arXiv:2312.02168, 2023NeurIPS 2023 Workshop on Distribution Shifts
- Trading Information between Latents in Hierarchical Variational AutoencodersIn International Conference on Learning Representations (ICLR), 2023
- Wat zei je? Detecting Out-of-Distribution Translations with Variational TransformersarXiv preprint arXiv:2006.08344, 2020Spotlight talk, NeurIPS 2019 Workshop on Bayesian Deep Learning