Christian Schroeder de Witt
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QMIX: monotonic value function factorisation for deep multi-agent reinforcement learning
T Rashid, M Samvelyan, CS De Witt, G Farquhar, J Foerster, S Whiteson
arXiv preprint arXiv:1803.11485, 2018
The ZX-calculus is incomplete for quantum mechanics
CS de Witt, V Zamdzhiev
arXiv preprint arXiv:1404.3633, 2014
The starcraft multi-agent challenge
M Samvelyan, T Rashid, C Schroeder de Witt, G Farquhar, N Nardelli, ...
Proceedings of the 18th International Conference on Autonomous Agents and …, 2019
Multi-Agent Common Knowledge Reinforcement Learning
CS de Witt, J Foerster, G Farquhar, P Torr, W Böhmer, S Whiteson
Advances in Neural Information Processing Systems, 9924-9935, 2019
Safe screening for support vector machines
J Zimmert, CS de Witt, G Kerg, M Kloft
NIPS 2015 Workshop on Optimization in Machine Learning (OPT), 2015
Hijacking Malaria Simulators with Probabilistic Programming
B Gram-Hansen, CS de Witt, T Rainforth, PHS Torr, YW Teh, AG Baydin
arXiv preprint arXiv:1905.12432, 2019
Amortized rejection sampling in universal probabilistic programming
S Naderiparizi, A Ścibior, A Munk, M Ghadiri, AG Baydin, B Gram-Hansen, ...
arXiv preprint arXiv:1910.09056, 2019
Efficient Bayesian Inference for Nested Simulators
B Gram-Hansen, CS de Witt, R Zinkov, S Naderiparizi, A Scibior, A Munk, ...
Stratospheric aerosol injection as a deep reinforcement learning problem
CS de Witt, T Hornigold
arXiv preprint arXiv:1905.07366, 2019
Simulation-Based Inference for Global Health Decisions
C Schroeder de Witt, B Gram-Hansen, N Nardelli, A Gambardella, ...
arXiv, arXiv: 2005.07062, 2020
Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control
CS de Witt, B Peng, PA Kamienny, P Torr, W Böhmer, S Whiteson
arXiv preprint arXiv:2003.06709, 2020
Artificial Intelligence & Climate Change: Supplementary Impact Report
T Walsh, A Evatt, CS de Witt
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Articles 1–12