Nathan Lambert
Nathan Lambert
Research Scientist, HuggingFace
Потвърден имейл адрес: huggingface.co - Начална страница
Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning
N Lambert, DS Drew, J Yaconelli, R Calandra, S Levine, KSJ Pister
IEEE Robotics and Automation Letters 4 (4), 4224-4230, 2019
Toward controlled flight of the ionocraft: a flying microrobot using electrohydrodynamic thrust with onboard sensing and no moving parts
D Drew, N Lambert, C Schindler, K Pister
IEEE Robotics and Automation Letters 3 (4), 2807-2813, 2018
On the importance of hyperparameter optimization for model-based reinforcement learning
B Zhang, R Rajan, L Pineda, N Lambert, A Biedenkapp, K Chua, F Hutter, ...
International Conference on Artificial Intelligence and Statistics, 4015-4023, 2021
Objective Mismatch in Model-based Reinforcement Learning
N Lambert, B Amos, O Yadan, R Calandra
Learning for Dynamics and Control (L4DC), 2020
Learning generalizable locomotion skills with hierarchical reinforcement learning
T Li, N Lambert, R Calandra, F Meier, A Rai
IEEE International Conference on Robotics and Automation (ICRA), 413-419, 2020
Enhanced lithium niobate pyroelectric ionizer for chip-scale ion mobility-based gas sensing
KB Vinayakumar, V Gund, N Lambert, S Lodha, A Lal
IEEE SENSORS, 1-3, 2016
Mbrl-lib: A modular library for model-based reinforcement learning
L Pineda, B Amos, A Zhang, NO Lambert, R Calandra
arXiv preprint arXiv:2104.10159, 2021
Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning
N Lambert, A Wilcox, H Zhang, K Pister, R Calandra
IEEE Conference on Decision and Control (CDC), 2880-2887, 2021
AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks
MK Andrus, S Dean, TK Gilbert, N Lambert, T Zick
IEEE Symposium on Technology and Society (ISTAS), 2021
Nonholonomic yaw control of an underactuated flying robot with model-based reinforcement learning
NO Lambert, CB Schindler, DS Drew, KSJ Pister
IEEE Robotics and Automation Letters 6 (2), 455-461, 2020
Reward Reports for Reinforcement Learning
TK Gilbert, S Dean, N Lambert, T Zick, A Snoswell
arXiv preprint arXiv:2204.10817, 2022
Investigating Compounding Prediction Errors in Learned Dynamics Models
N Lambert, K Pister, R Calandra
arXiv preprint arXiv:2203.09637, 2022
Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems
TK Gilbert, S Dean, T Zick, N Lambert
Center for Long Term Cybersecurity Whitepaper Series, 2022
Axes for sociotechnical inquiry in AI research
S Dean, TK Gilbert, N Lambert, T Zick
IEEE Transactions on Technology and Society 2 (2), 62-70, 2021
The Challenges of Exploration for Offline Reinforcement Learning
N Lambert, M Wulfmeier, W Whitney, A Byravan, M Bloesch, V Dasagi, ...
arXiv preprint arXiv:2201.11861, 2022
Predicting Flying Robot Dynamics with Deep Learning
B Li, N Lambert
Journal of Student Research 10 (3), 2021
BotNet: A Simulator for Studying the Effects of Accurate Communication Models on Multi-agent and Swarm Control
M Selden, J Zhou, F Campos, N Lambert, D Drew, KSJ Pister
IEEE International Symposium on Multi-Robot and Multi-Agent Systems (MRS …, 2021
Learning for Microrobot Exploration: Model-based Locomotion, Sparse-robust Navigation, and Low-power Deep Classification
N Lambert, F Toddywala, B Liao, E Zhu, L Lee, K Pister
IEEE Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), 2020
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