Erik Jenner

According to our database, Erik Jenner authored at least 7 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning.

Leon Lang, Davis Foote, Stuart Russell, Anca D. Dragan, Erik Jenner, Scott Emmons

CoRR, 2024

2023

STARC: A General Framework For Quantifying Differences Between Reward Functions.

Joar Skalse, Lucy Farnik, Sumeet Ramesh Motwani, Erik Jenner, Adam Gleave, Alessandro Abate

CoRR, 2023

2022

imitation: Clean Imitation Learning Implementations.

Adam Gleave, Mohammad Taufeeque, Juan Rocamonde, Erik Jenner, Steven H. Wang, Sam Toyer, Maximilian Ernestus, Nora Belrose, Scott Emmons, Stuart Russell

CoRR, 2022

Calculus on MDPs: Potential Shaping as a Gradient.

Erik Jenner, Herke van Hoof, Adam Gleave

CoRR, 2022

Preprocessing Reward Functions for Interpretability.

Erik Jenner, Adam Gleave

CoRR, 2022

Steerable Partial Differential Operators for Equivariant Neural Networks.

Erik Jenner, Maurice Weiler

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice.

Erik Jenner, Enrique Fita Sanmartín, Fred A. Hamprecht

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021