Noah Y. Siegel
Cited by
Cited by
Critic regularized regression
Z Wang, A Novikov, K Zolna, JS Merel, JT Springenberg, SE Reed, ...
Advances in Neural Information Processing Systems 33, 7768-7778, 2020
Keep doing what worked: Behavioral modelling priors for offline reinforcement learning
NY Siegel, JT Springenberg, F Berkenkamp, A Abdolmaleki, M Neunert, ...
arXiv preprint arXiv:2002.08396, 2020
Figureseer: Parsing result-figures in research papers
N Siegel, Z Horvitz, R Levin, S Divvala, A Farhadi
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
Extracting scientific figures with distantly supervised neural networks
N Siegel, N Lourie, R Power, W Ammar
Proceedings of the 18th ACM/IEEE on joint conference on digital libraries …, 2018
From motor control to team play in simulated humanoid football
S Liu, G Lever, Z Wang, J Merel, SMA Eslami, D Hennes, WM Czarnecki, ...
Science Robotics 7 (69), eabo0235, 2022
Solving math word problems with process-and outcome-based feedback
J Uesato, N Kushman, R Kumar, F Song, N Siegel, L Wang, A Creswell, ...
arXiv preprint arXiv:2211.14275, 2022
Learning agile soccer skills for a bipedal robot with deep reinforcement learning
T Haarnoja, B Moran, G Lever, SH Huang, D Tirumala, J Humplik, ...
Science Robotics 9 (89), eadi8022, 2024
Data-efficient hindsight off-policy option learning
M Wulfmeier, D Rao, R Hafner, T Lampe, A Abdolmaleki, T Hertweck, ...
International Conference on Machine Learning, 11340-11350, 2021
Imagined value gradients: Model-based policy optimization with tranferable latent dynamics models
A Byravan, JT Springenberg, A Abdolmaleki, R Hafner, M Neunert, ...
Conference on Robot Learning, 566-589, 2020
Imitate and repurpose: Learning reusable robot movement skills from human and animal behaviors
S Bohez, S Tunyasuvunakool, P Brakel, F Sadeghi, L Hasenclever, ...
arXiv preprint arXiv:2203.17138, 2022
Compositional transfer in hierarchical reinforcement learning
M Wulfmeier, A Abdolmaleki, R Hafner, JT Springenberg, M Neunert, ...
arXiv preprint arXiv:1906.11228, 2019
Regularized hierarchical policies for compositional transfer in robotics
M Wulfmeier, A Abdolmaleki, R Hafner, JT Springenberg, M Neunert, ...
arXiv preprint arXiv:1906.11228, 2019
Towards real robot learning in the wild: A case study in bipedal locomotion
M Bloesch, J Humplik, V Patraucean, R Hafner, T Haarnoja, A Byravan, ...
Conference on Robot Learning, 1502-1511, 2022
Simple sensor intentions for exploration
T Hertweck, M Riedmiller, M Bloesch, JT Springenberg, N Siegel, ...
arXiv preprint arXiv:2005.07541, 2020
Challenging Systematic Prejudices: An Investigation into Bias Against Women and Girls
D Van Niekerk, M Peréz-Ortiz, J Shawe-Taylor, D Orlic, J Kay, N Siegel, ...
Solving math word problems with process-based and outcome-based feedback
J Uesato, N Kushman, R Kumar, HF Song, NY Siegel, L Wang, A Creswell, ...
Understanding charts in research papers: A learning approach
N Siegel
Technical report, 2015
The Effect of Model Size on LLM Post-hoc Explainability via LIME
H Heyen, A Widdicombe, NY Siegel, M Perez-Ortiz, P Treleaven
arXiv preprint arXiv:2405.05348, 2024
On scalable oversight with weak LLMs judging strong LLMs
Z Kenton, NY Siegel, J Kramár, J Brown-Cohen, S Albanie, J Bulian, ...
arXiv preprint arXiv:2407.04622, 2024
The Probabilities Also Matter: A More Faithful Metric for Faithfulness of Free-Text Explanations in Large Language Models
NY Siegel, OM Camburu, N Heess, M Perez-Ortiz
arXiv preprint arXiv:2404.03189, 2024
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