NIPS 2017

Yee Whye Teh will give a Breiman keynote lecture at NIPS 2017 entitled On Bayesian Deep Learning and Deep Bayesian Learning.

6 papers co-authored by the OxCSML group members have been accepted to the main program of NIPS 2017:

• Filtering Variational Objectives
  Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Mohammad Norouzi, Andriy Mnih, Arnaud Doucet, Yee Whye Teh

• REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
  George Tucker, Andriy Mnih, Chris J. Maddison, John Lawson, Jascha Sohl-Dickstein

• DisTraL: Robust multitask reinforcement learning
  Yee Whye Teh, Victor Bapst, Razvan Pascanu, Nicolas Heess, John Quan, James Kirkpatrick, Wojciech M. Czarnecki, Raia Hadsell

• Testing and Learning on Distributions with Symmetric Noise Invariance
  Ho Chung Leon Law, Christopher Yau, Dino Sejdinovic

• Accelerated consensus via Min-Sum Splitting
  Patrick Rebeschini, Sekhar Tatikonda

• Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling
  Andrei-Cristian Barbos, Francois Caron, Jean-Francois Giovannelli, Arnaud Doucet