I am a third year Ph.D student at Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, working with Charles Sutton. Before this, I completed my master supervised by Zoubin Ghahramani at Cambridge University Engineering Department. Research topics I'm interested in include approximate inference, (deep) generative models, probabilistic programming - together with their applications to fields like neuroscience and intuitive physics. Mentioning interests, I also love cats.
I'm a member of the core team of the Turing probabilistic programming language. I write efficient and robust software on Hamiltonian Monte Carlo methods in Julia (AdvancedHMC.jl).
Akash Srivastava*, Kai Xu*, Michael U. Gutmann and Charles Sutton. "Generative ratio matching network.", To appear in International Conference on Learning Representations, 2020. (OpenReview)
Cole L. Hurwitz, Kai Xu, Akash Srivastava, Alessio Paolo Buccino and Matthias Hennig. "Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference.", Neural Information Processing Systems, 2019. (arXiv, abs, pdf)
Kai Xu, Akash Srivastava and Charles Sutton. "Variational Russian Roulette for Deep Bayesian Nonparametrics.", International Conference on Machine Learning, 2019. (abs, pdf, suppl, code)
Hong Ge, Kai Xu, and Zoubin Ghahramani. "Turing: A Language for Flexible Probabilistic Inference.", International Conference on Artificial Intelligence and Statistics, 2018. (abs, pdf, code, website)
Kai Xu, Hong Ge, Will Tebbutt, Mohamed Tarek, Martin Trapp, Zoubin Ghahramani. "AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms.", Symposium on Advances in Approximate Bayesian Inference, 2019. (abs, pdf, OpenReview)
Tor Erlend Fjelde, Kai Xu, Mohamed Tarek, Sharan Yalburgi, Hong Ge. "Bijectors.jl: Flexible transformations for probability distributions.", Symposium on Advances in Approximate Bayesian Inference, 2019. (abs, pdf, OpenReview)
Mohamed Tarek, Kai Xu, Martin Trapp, Hong Ge, Zoubin Ghahramani "DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models.", arXiv preprint arXiv: 2002.02702, 2020. (arXiv)
Kai Xu, Dae Hoon Park, Yi Chang and Charles Sutton. "Interpreting Deep Classifiers by Visual Distillation of Dark Knowledge.", arXiv preprint arXiv: 1803.04042, 2018. (arXiv, pdf, demo, code, website)
Turing.jl: The Turing language for probabilistic machine learning and Bayesian statistics
AdvancedHMC.jl: Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
Links: GitHub
DensityRatioEstimation.jl: A Julia package for density ratio estimation
Links: GitHub
Presenter for "The Turing Language for Probabilistic Programming." at Julia Lab, MIT, MA, USA in June 2019
Presenter for "Variational Russian Roulette for Deep Bayesian Nonparametrics." at MIT-IBM Research, MIT, CA, USA in June 2019.
Presenter for "Variational Russian Roulette for Deep Bayesian Nonparametrics." at The 36th International Conference on Machine Learning, Long Beach, CA, USA in June 2019.
Copresenter for "The Turing Language for Probabilistic Programming." at The Inaugural International Conference on Probabilistic Programming, MIT, MA, USA in October 2018
Presenter for "Turing: a Fresh Approach to Probabilistic Programming." at JuliaCon 2017, Berkeley, CA, USA in June 2017 (video)
Google Summer of Code / Mentor
Jun. 2019 - Aug. 2019
University of Edinburgh / Tutor for Probabilistic Modelling and Reasoning
Jan. 2019 - Apr. 2019, Edinburgh, United Kingdom
University of Edinburgh / Teaching Assistant for Machine Learning and Pattern Recognition
Sep. 2018 - Dec. 2018, Edinburgh, United Kingdom
Apple / Machine Learning Intern
May 2018 - Aug. 2018, Cambridge, United Kingdom
University of Edinburgh / Teaching Assistant for Design Informatics
Oct. 2017 - Dec. 2017, Edinburgh, United Kingdom
University fo Cambridge / Research Assistant at Machine Learning Group
Nov. 2016 - Jul. 2017, Cambridge, United Kingdom
The Brain Charity / Voluntary Software Developer
Aug. 2014 - Jul. 2015, Liverpool, United Kingdom
University of Edinburgh / Ph.D in Informatics: Machine Learning
Sep. 2017 - PRESENT, Edinburgh, United Kingdom
University of Cambridge / M.Phil in Machine Learning, Speech & Language Technology
Oct. 2015 - Sep. 2016, Cambridge, United Kingdom
University of Liverpool / B.Eng in Computer Science and Electronic Engineering
Sep. 2013 - Jun. 2015, Liverpool, United Kingdom
Xi'an Jiaotong-Liverpool University / B.Eng in Computer Science & Technology
Sep. 2011 - Jun. 2013, Suzhou, China
Mobile Robot Control using ROS (poster)
DBD Plasma Reactor Power Monitoring System
Wireless Brain-Computer Interface for Game Control (video)
FlatShare (code)
