Chris J. Maddison
Probabilistic inference, Monte Carlo methods, neural networks, point processes
I am a DPhil student of statistics at the University of Oxford supervised by Yee Whye Teh and Arnaud Doucet. I also spend two days a week as a Research Scientist at DeepMind. Previously, I received my MSc. from the University of Toronto supervised by Geoffrey Hinton. I was one of the primary contributors to the AlphaGo project.
Publications
2019

E. Mathieu
,
C. Le Lan
,
C. J. Maddison
,
R. Tomioka
,
Y. W. Teh
,
Continuous Hierarchical Representations with Poincaré Variational AutoEncoders, in Advances in Neural Information Processing Systems 32, 2019, 12565–12576.
2018

T. Rainforth
,
A. R. Kosiorek
,
T. A. Le
,
C. J. Maddison
,
M. Igl
,
F. Wood
,
Y. W. Teh
,
Tighter Variational Bounds are Not Necessarily Better, in International Conference on Machine Learning (ICML), 2018.
Project: bigbayes
2017

C. J. Maddison
,
D. Lawson
,
G. Tucker
,
N. Heess
,
M. Norouzi
,
A. Mnih
,
A. Doucet
,
Y. W. Teh
,
Filtering Variational Objectives, in Advances in Neural Information Processing Systems (NeurIPS), 2017.
Project: deepmind 
C. J. Maddison
,
A. Mnih
,
Y. W. Teh
,
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables, in International Conference on Learning Representations (ICLR), 2017.
Project: deepmind 
C. J. Maddison
,
D. Lawson
,
G. Tucker
,
N. Heess
,
M. Norouzi
,
A. Mnih
,
A. Doucet
,
Y. W. Teh
,
Particle Value Functions, in ICLR 2017 Workshop Proceedings, 2017.
Project: deepmind
2016

C. J. Maddison
,
A Poisson process model for Monte Carlo, in Perturbation, Optimization, and Statistics, T. Hazan, G. Papandreou, and D. Tarlow, Eds. MIT Press, 2016.

D. Silver
,
A. Huang
,
C. J. Maddison
,
A. Guez
,
L. Sifre
,
G. Driessche
,
J. Schrittwieser
,
I. Antonoglou
,
V. Panneershelvam
,
M. Lanctot
,
S. Dieleman
,
D. Grewe
,
J. Nham
,
N. Kalchbrenner
,
I. Sutskever
,
T. Lillicrap
,
M. Leach
,
K. Kavukcuoglu
,
T. Graepel
,
D. Hassabis
,
Mastering the game of Go with deep neural networks and tree search, Nature, vol. 529, no. 7587, 484–489, 2016.
2015

C. J. Maddison
,
A. Huang
,
I. Sutskever
,
D. Silver
,
Move Evaluation in Go Using Deep Convolutional Neural Networks, in International Conference on Learning Representations, 2015.
2014

C. J. Maddison
,
D. Tarlow
,
Structured Generative Models of Natural Source Code, in Proceedings of the 31st International Conference on Machine Learning, 2014.

C. J. Maddison
,
D. Tarlow
,
T. Minka
,
A* Sampling, in Advances in Neural Information Processing Systems 27, 2014.
2013

R. Grosse
,
C. J. Maddison
,
R. Salakhutdinov
,
Annealing Between Distributions by Averaging Moments, in Advances in Neural Information Processing Systems 26, 2013.
2012

S. A. Heimovics
,
N. H. Prior
,
C. J. Maddison
,
K. K. Soma
,
Rapid and Widespread Effects of 17betaestradiol on Intracellular Signaling in the Male Songbird Brain: A Seasonal Comparison, Endocrinology, vol. 153, no. 3, 1364–1376, 2012.

C. J. Maddison
,
R. C. Anderson
,
N. H. Prior
,
M. D. Taves
,
K. K. Soma
,
Soft song during aggressive interactions: Seasonal changes and endocrine correlates in song sparrows, Hormones and Behavior, vol. 62, no. 4, 455–463, 2012.