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Mark Rowland
Mark Rowland
Research Scientist, Google DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Distributional reinforcement learning with quantile regression
W Dabney, M Rowland, M Bellemare, R Munos
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
6712018
Gaussian process behaviour in wide deep neural networks
AGG Matthews, M Rowland, J Hron, RE Turner, Z Ghahramani
arXiv preprint arXiv:1804.11271, 2018
483*2018
Black-box -divergence Minimization
JM Hernández-Lobato, Y Li, M Rowland, D Hernández-Lobato, T Bui, ...
arXiv preprint arXiv:1511.03243, 2015
2492015
Revisiting fundamentals of experience replay
W Fedus, P Ramachandran, R Agarwal, Y Bengio, H Larochelle, ...
International Conference on Machine Learning, 3061-3071, 2020
2172020
Structured evolution with compact architectures for scalable policy optimization
K Choromanski, M Rowland, V Sindhwani, R Turner, A Weller
International Conference on Machine Learning, 970-978, 2018
1352018
α-Rank: Multi-Agent Evaluation by Evolution
S Omidshafiei, C Papadimitriou, G Piliouras, K Tuyls, M Rowland, ...
Scientific reports 9 (1), 9937, 2019
1112019
An analysis of categorical distributional reinforcement learning
M Rowland, M Bellemare, W Dabney, R Munos, YW Teh
International Conference on Artificial Intelligence and Statistics, 29-37, 2018
1112018
A generalized training approach for multiagent learning
P Muller, S Omidshafiei, M Rowland, K Tuyls, J Perolat, S Liu, D Hennes, ...
arXiv preprint arXiv:1909.12823, 2019
882019
Mastering the game of Stratego with model-free multiagent reinforcement learning
J Perolat, B De Vylder, D Hennes, E Tarassov, F Strub, V de Boer, ...
Science 378 (6623), 990-996, 2022
852022
The unreasonable effectiveness of structured random orthogonal embeddings
KM Choromanski, M Rowland, A Weller
Advances in neural information processing systems 30, 2017
832017
Statistics and samples in distributional reinforcement learning
M Rowland, R Dadashi, S Kumar, R Munos, MG Bellemare, W Dabney
International Conference on Machine Learning, 5528-5536, 2019
802019
Distributional reinforcement learning
MG Bellemare, W Dabney, M Rowland
MIT Press, 2023
742023
Meta-learning of sequential strategies
PA Ortega, JX Wang, M Rowland, T Genewein, Z Kurth-Nelson, ...
arXiv preprint arXiv:1905.03030, 2019
732019
Game Plan: What AI can do for Football, and What Football can do for AI
K Tuyls, S Omidshafiei, P Muller, Z Wang, J Connor, D Hennes, I Graham, ...
Journal of Artificial Intelligence Research 71, 41-88, 2021
722021
From Poincaré recurrence to convergence in imperfect information games: Finding equilibrium via regularization
J Perolat, R Munos, JB Lespiau, S Omidshafiei, M Rowland, P Ortega, ...
International Conference on Machine Learning, 8525-8535, 2021
632021
The value-improvement path: Towards better representations for reinforcement learning
W Dabney, A Barreto, M Rowland, R Dadashi, J Quan, MG Bellemare, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 7160-7168, 2021
572021
On the effect of auxiliary tasks on representation dynamics
C Lyle, M Rowland, G Ostrovski, W Dabney
International Conference on Artificial Intelligence and Statistics, 1-9, 2021
552021
Understanding and preventing capacity loss in reinforcement learning
C Lyle, M Rowland, W Dabney
arXiv preprint arXiv:2204.09560, 2022
422022
Orthogonal estimation of wasserstein distances
M Rowland, J Hron, Y Tang, K Choromanski, T Sarlos, A Weller
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
422019
Magnetic hamiltonian monte carlo
N Tripuraneni, M Rowland, Z Ghahramani, R Turner
International Conference on Machine Learning, 3453-3461, 2017
422017
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