| imitation: Clean imitation learning implementations A Gleave, M Taufeeque, J Rocamonde, E Jenner, SH Wang, S Toyer, ... arXiv preprint arXiv:2211.11972, 2022 | 27 | 2022 |
| Steerable Partial Differential Operators for Equivariant Neural Networks E Jenner, M Weiler ICLR, 2022 | 24 | 2022 |
| Preprocessing Reward Functions for Interpretability E Jenner, A Gleave NeurIPS Cooperative AI workshop, 2021 | 8 | 2021 |
| STARC: A General Framework For Quantifying Differences Between Reward Functions J Skalse, L Farnik, SR Motwani, E Jenner, A Gleave, A Abate arXiv preprint arXiv:2309.15257, 2023 | 3 | 2023 |
| Calculus on MDPs: Potential Shaping as a Gradient E Jenner, H van Hoof, A Gleave arXiv preprint arXiv:2208.09570, 2022 | 1 | 2022 |
| A general framework for reward function distances E Jenner, JMV Skalse, A Gleave NeurIPS ML Safety Workshop, 2022 | 1 | 2022 |
| Foundational Challenges in Assuring Alignment and Safety of Large Language Models U Anwar, A Saparov, J Rando, D Paleka, M Turpin, P Hase, ES Lubana, ... arXiv preprint arXiv:2404.09932, 2024 | | 2024 |
| When Your AI Deceives You: Challenges with Partial Observability of Human Evaluators in Reward Learning L Lang, D Foote, S Russell, A Dragan, E Jenner, S Emmons arXiv preprint arXiv:2402.17747, 2024 | | 2024 |
| Replication: Fairness without demographics through Adversarially Reweighted Learning E Jenner, T Lieberum, FP Nolte, N Rutsch | | 2021 |
| Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice E Jenner, EF Sanmartín, FA Hamprecht Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | | 2021 |
Adam GleaveCEO at FAR AIVerified email at far.ai
