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Mark Rowland
Mark Rowland
Research Scientist, 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
4252018
Gaussian process behaviour in wide deep neural networks
AGG Matthews, M Rowland, J Hron, RE Turner, Z Ghahramani
arXiv preprint arXiv:1804.11271, 2018
382*2018
Black-box -divergence Minimization
JM Hernández-Lobato, Y Li, M Rowland, D Hernández-Lobato, T Bui, ...
arXiv preprint arXiv:1511.03243, 2015
2122015
Revisiting fundamentals of experience replay
W Fedus, P Ramachandran, R Agarwal, Y Bengio, H Larochelle, ...
International Conference on Machine Learning, 3061-3071, 2020
1092020
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
1042018
α-rank: Multi-agent evaluation by evolution
S Omidshafiei, C Papadimitriou, G Piliouras, K Tuyls, M Rowland, ...
Scientific reports 9 (1), 1-29, 2019
902019
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
852018
The unreasonable effectiveness of structured random orthogonal embeddings
KM Choromanski, M Rowland, A Weller
Advances in neural information processing systems 30, 2017
652017
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
602019
Meta-learning of sequential strategies
PA Ortega, JX Wang, M Rowland, T Genewein, Z Kurth-Nelson, ...
arXiv preprint arXiv:1905.03030, 2019
522019
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
492019
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
422021
Magnetic hamiltonian monte carlo
N Tripuraneni, M Rowland, Z Ghahramani, R Turner
International Conference on Machine Learning, 3453-3461, 2017
372017
Multiagent evaluation under incomplete information
M Rowland, S Omidshafiei, K Tuyls, J Perolat, M Valko, G Piliouras, ...
Advances in Neural Information Processing Systems 32, 2019
302019
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
292021
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
282021
The geometry of random features
K Choromanski, M Rowland, T Sarlós, V Sindhwani, R Turner, A Weller
International Conference on Artificial Intelligence and Statistics, 1-9, 2018
282018
Orthogonal estimation of wasserstein distances
M Rowland, J Hron, Y Tang, K Choromanski, T Sarlós, A Weller
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
272019
Geometrically coupled monte carlo sampling
M Rowland, KM Choromanski, F Chalus, A Pacchiano, T Sarlos, ...
Advances in Neural Information Processing Systems 31, 2018
252018
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
242021
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