| When will AI exceed human performance? Evidence from AI experts K Grace, J Salvatier, A Dafoe, B Zhang, O Evans Journal of Artificial Intelligence Research 62, 729-754, 2018 | 453 | 2018 |
| The malicious use of artificial intelligence: Forecasting, prevention, and mitigation M Brundage, S Avin, J Clark, H Toner, P Eckersley, B Garfinkel, A Dafoe, ... arXiv preprint arXiv:1802.07228, 2018 | 403* | 2018 |
| Help or hinder: Bayesian models of social goal inference TD Ullman, CL Baker, O Macindoe, O Evans, ND Goodman, ... MASSACHUSETTS INST OF TECH CAMBRIDGE DEPT OF BRAIN AND COGNITIVE SCIENCES, 2009 | 139 | 2009 |
| Trial without error: Towards safe reinforcement learning via human intervention W Saunders, G Sastry, A Stuhlmueller, O Evans arXiv preprint arXiv:1707.05173, 2017 | 110 | 2017 |
| Learning the Preferences of Ignorant, Inconsistent Agents O Evans, A Stuhlmüller, ND Goodman Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-2016), 2016 | 80 | 2016 |
| Agent-Agnostic Human-in-the-Loop Reinforcement Learning D Abel, J Salvatier, A Stuhlmüller, O Evans arXiv:1701.0407, 2017 | 35 | 2017 |
| Learning the Preferences of Bounded Agents O Evans, A Stuhlmüller, ND Goodman Advances in Neural Information Processing Systems (Bounded Optimality Workshop), 2015 | 25 | 2015 |
| Learning structured preferences O Evans, L Bergen, JB Tenenbaum Proceedings of the 32nd annual conference of the cognitive science society, 2010 | 18* | 2010 |
| Estimating household transmission of SARS-CoV-2 M Curmei, A Ilyas, O Evans, J Steinhardt medRxiv, 2020 | 15 | 2020 |
| Modeling Agents with Probabilistic Programs O Evans, A Stuhlmüller, J Salvatier, D Filan agentmodels.org, 2017 | 10* | 2017 |
| Active Reinforcement Learning: Observing Rewards at a Cost D Krueger, J Leike, O Evans, J Salvatier NIPS 2016 Workshop, 2016 | 10* | 2016 |
| Modelling the Health and Economic Impacts of Population-Wide Testing, Contact Tracing and Isolation (PTTI) Strategies for COVID-19 in the UK T Colbourn, W Waites, J Panovska-Griffiths, D Manheim, S Sturniolo, ... SSRN, 2020 | 9 | 2020 |
| Predicting Human Deliberative Judgments with Machine Learning O Evans, A Stuhlmüller, C Cundy, R Carey, Z Kenton, T McGrath, ... FHI Technical Report, 2018 | 8 | 2018 |
| Generalizing from a few environments in safety-critical reinforcement learning Z Kenton, A Filos, O Evans, Y Gal arXiv preprint arXiv:1907.01475, 2019 | 7 | 2019 |
| Active reinforcement learning with monte-carlo tree search S Schulze, O Evans arXiv preprint arXiv:1803.04926, 2018 | 5 | 2018 |
| Model mis-specification and inverse reinforcement learning J Steinhardt, O Evans | 5 | 2017 |
| Sensory Optimization: Neural Networks as a Model for Understanding and Creating Art O Evans arXiv preprint arXiv:1911.07068, 2019 | 1 | 2019 |
| Modelling the health and economic impacts of different testing and tracing strategies for COVID-19 in the UK [version 1; peer review: awaiting peer review] T Colbourn, W Waites, D Manheim, D Foster, S Sturniolo, M Sculpher, ... F1000Research 9, 2020 | | 2020 |
| Machine Learning Projects for Iterated Distillation and Amplification O Evans, W Saunders, A Stuhlmüller FHI Technical Report, 2019 | | 2019 |
| Bayesian computational models for inferring preferences OR Evans Massachusetts Institute of Technology, 2015 | | 2015 |
Andreas StuhlmüllerOughtVerified email at ought.org
