papers
Publications (11)
stat.ML2019
Statistics and Samples in Distributional Reinforcement Learning
Mark Rowland, Robert Dadashi, Saurabh Kumar +3
stat.ML2018
Antithetic and Monte Carlo kernel estimators for partial rankings
Maria Lomeli, Mark Rowland, Arthur Gretton +1
cs.AI2017
Distributional Reinforcement Learning with Quantile Regression
Will Dabney, Mark Rowland, Marc G. Bellemare +1
stat.ML2018
The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings
Krzysztof Choromanski, Mark Rowland, Adrian Weller
cs.LG2018
Structured Evolution with Compact Architectures for Scalable Policy Optimization
Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani +2
cs.LG2019
Meta-learning of Sequential Strategies
Pedro A. Ortega, Jane X. Wang, Mark Rowland +21
stat.ML2019
Orthogonal Estimation of Wasserstein Distances
Mark Rowland, Jiri Hron, Yunhao Tang +3
stat.ML2016
Black-box $α$-divergence Minimization
José Miguel Hernández-Lobato, Yingzhen Li, Mark Rowland +3
stat.ML2018
Gaussian Process Behaviour in Wide Deep Neural Networks
Alexander G. de G. Matthews, Mark Rowland, Jiri Hron +2
stat.ML2017
Magnetic Hamiltonian Monte Carlo
Nilesh Tripuraneni, Mark Rowland, Zoubin Ghahramani +1
stat.ML2018
An Analysis of Categorical Distributional Reinforcement Learning
Mark Rowland, Marc G. Bellemare, Will Dabney +2