Markus Kunesch
Markus Kunesch
Verified email at
Cited by
Cited by
GRChombo: numerical relativity with adaptive mesh refinement
K Clough, P Figueras, H Finkel, M Kunesch, EA Lim, S Tunyasuvunakool
Classical and Quantum Gravity 32 (24), 245011, 2015
End point of black ring instabilities and the weak cosmic censorship conjecture
P Figueras, M Kunesch, S Tunyasuvunakool
Physical review letters 116 (7), 071102, 2016
End point of the ultraspinning instability and violation of cosmic censorship
P Figueras, M Kunesch, L Lehner, S Tunyasuvunakool
Physical Review Letters 118 (15), 151103, 2017
The DeepMind JAX Ecosystem, 2020
I Babuschkin, K Baumli, A Bell, S Bhupatiraju, J Bruce, P Buchlovsky, ...
URL http://github. com/deepmind, 2010
GRChombo: An adaptable numerical relativity code for fundamental physics
T Andrade, LA Salo, JC Aurrekoetxea, J Bamber, K Clough, R Croft, ...
arXiv preprint arXiv:2201.03458, 2022
Shaking the foundations: delusions in sequence models for interaction and control
PA Ortega, M Kunesch, G Delétang, T Genewein, J Grau-Moya, J Veness, ...
arXiv preprint arXiv:2110.10819, 2021
End point of nonaxisymmetric black hole instabilities in higher dimensions
H Bantilan, P Figueras, M Kunesch, RP Macedo
Physical Review D 100 (8), 086014, 2019
Nonspherically symmetric collapse in asymptotically AdS spacetimes
H Bantilan, P Figueras, M Kunesch, P Romatschke
Physical review letters 119 (19), 191103, 2017
Dimensional reduction in numerical relativity: Modified cartoon formalism and regularization
WG Cook, P Figueras, M Kunesch, U Sperhake, S Tunyasuvunakool
International Journal of Modern Physics D 25 (09), 1641013, 2016
Human-interpretable model explainability on high-dimensional data
D de Mijolla, C Frye, M Kunesch, J Mansir, I Feige
arXiv preprint arXiv:2010.07384, 2020
Causal analysis of agent behavior for ai safety
G Déletang, J Grau-Moya, M Martic, T Genewein, T McGrath, V Mikulik, ...
arXiv preprint arXiv:2103.03938, 2021
Model-free risk-sensitive reinforcement learning
G Delétang, J Grau-Moya, M Kunesch, T Genewein, R Brekelmans, ...
arXiv preprint arXiv:2111.02907, 2021
Your policy regularizer is secretly an adversary
R Brekelmans, T Genewein, J Grau-Moya, G Delétang, M Kunesch, ...
arXiv preprint arXiv:2203.12592, 2022
Numerical simulations of instabilities in general relativity
M Kunesch
University of Cambridge, 2018
Representation in AI Evaluations
AS Bergman, LA Hendricks, M Rauh, B Wu, W Agnew, M Kunesch, I Duan, ...
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023
The puzzle of evaluating moral cognition in artificial agents
MG Reinecke, Y Mao, M Kunesch, EA Duéñez‐Guzmán, J Haas, JZ Leibo
Cognitive Science 47 (8), e13315, 2023
Doing the right thing for the right reason: Evaluating artificial moral cognition by probing cost insensitivity
Y Mao, MG Reinecke, M Kunesch, EA Duéñez-Guzmán, R Comanescu, ...
arXiv preprint arXiv:2305.18269, 2023
GRChombo: Numerical relativity simulator
T Andrade, L Salo, J Aurrekoetxea, J Bamber, K Clough, R Croft, ...
Astrophysics Source Code Library, ascl: 2306.039, 2023
Beyond Bayes-optimality: meta-learning what you know you don't know
J Grau-Moya, G Delétang, M Kunesch, T Genewein, E Catt, K Li, A Ruoss, ...
arXiv preprint arXiv:2209.15618, 2022
Stochastic Approximation of Gaussian Free Energy for Risk-Sensitive Reinforcement Learning
G Delétang, J Grau-Moya, M Kunesch, T Genewein, R Brekelmans, ...
The system can't perform the operation now. Try again later.
Articles 1–20