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Tim Franzmeyer
Tim Franzmeyer
Verified email at robots.ox.ac.uk - Homepage
Title
Cited by
Cited by
Year
Learn what matters: cross-domain imitation learning with task-relevant embeddings
T Franzmeyer, PHS Torr, JF Henriques
Neural Information Processing Systems (NeurIPS), 2022
102022
Extracting Reward Functions from Diffusion Models
F Nuti*, T Franzmeyer*, JF Henriques
arXiv preprint arXiv:2306.01804, 2023
72023
Learning Altruistic Behaviours in Reinforcement Learning without External Rewards
T Franzmeyer, M Malinowski, JF Henriques
International Conference on Learning Representations (ICLR), 2022
72022
Illusory attacks: Detectability matters in adversarial attacks on sequential decision-makers
T Franzmeyer, S McAleer, JF Henriques, JN Foerster, PHS Torr, A Bibi, ...
arXiv preprint arXiv:2207.10170, 2022
4*2022
Select to Perfect: Imitating desired behavior from large multi-agent data
T Franzmeyer, E Elkind, P Torr, J Foerster, J Henriques
arXiv preprint arXiv:2405.03735, 2024
12024
HelloFresh: LLM Evaluations on Streams of Real-World Human Editorial Actions across X Community Notes and Wikipedia edits
T Franzmeyer, A Shtedritski, S Albanie, P Torr, JF Henriques, JN Foerster
arXiv preprint arXiv:2406.03428, 2024
2024
Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection
L Nasvytis, K Sandbrink, J Foerster, T Franzmeyer, CS de Witt
arXiv preprint arXiv:2404.07099, 2024
2024
Scalable Biologically-Aware Skeleton Generation for Connectomic Volumes
B Matejek, T Franzmeyer, D Wei, X Wang, J Zhao, K Palįgyi, JW Lichtman, ...
IEEE transactions on medical imaging 41 (9), 2360-2370, 2022
2022
Illusory Attacks: Information-theoretic detectability matters in adversarial attacks
T Franzmeyer, SM McAleer, JF Henriques, JN Foerster, P Torr, A Bibi, ...
The Twelfth International Conference on Learning Representations, 0
Who to imitate: Imitating desired behavior from diverse multi-agent datasets
T Franzmeyer, JN Foerster, E Elkind, P Torr, JF Henriques
ICML 2023 Workshop The Many Facets of Preference-Based Learning, 0
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Articles 1–10