Chris J. Maddison

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

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, arXiv preprint arXiv:1802.04537, 2018.

2017

  • 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.
  • 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.
  • 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 (NIPS), 2017.

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 17-beta-estradiol 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.