NIPS 2016 participation
Many group members will be at NIPS 2016 presenting work at the main conference and workshops.
- Tamara Fernández will be presenting “Gaussian Processes for Survival Analysis” at the main conference.
- Stefan Webb will be presenting “A Tighter Monte Carlo Objective with Renyi alpha-Divergence Measures” at the Bayesian Deep Learning workshop.
- Hyunjik Kim will be presenting “Scalable Structure Discovery in Regression using Gaussian Processes” at the Practical Bayesian Nonparametrics workshop.
- Leonard Hasenclaver, Stefan Webb and Thibaut Lienart will be presenting “Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server” at the Advances in Approximate Bayesian Inference and Bayesian Deep Learning workshops.
- Valerio Perrone and Xiaoyu Lu will be presenting “Relativistic Monte Carlo” at the Bayesian Deep Learning workshop.
- Konstantina Palla will be presenting “Bayesian nonparametrics for Sparse Dynamic Networks”, Xiaoyu Lu will be presenting “Tucker Gaussian Process for Regression and Collaborative Filtering”, Qinyi Zhang will be presenting “Large-Scale Kernel Methods for Independence Testing” and Jovana Mitrovic will be presenting “Disentangling the Factors of Variation at Initialization In Neural Networks” at the Women in Machine Learning Workshop.