Funder
National Science Foundation
Office of Naval Research
Publisher
Springer Science and Business Media LLC
Reference50 articles.
1. Ajay, A., Wu, J., Fazeli, N., Bauza, M., Kaelbling, L. P., Tenenbaum, J. B., et al. (2018). Augmenting physical simulators with stochastic neural networks: Case study of planar pushing and bouncing. In International conference on intelligent robots and systems (IROS).
2. Allevato, A., Schaertl Short, E., Pryor, M., & Thomaz, A. L. (2019). TuneNet: One-shot residual tuning for system identification and sim-to-real robot task transfer. CoRR arXiv:1907.11200v3.
3. Ayusawa, K., Venture, G., & Nakamura, Y. (2013). Identifiability and identification of inertial parameters using the underactuated base-link dynamics for legged multibody systems. The International Journal of Robotics Research, 33, 446–468. https://doi.org/10.1177/0278364913495932.
4. Bottou, L. (2010). Large-scale machine learning with stochastic gradient descent. In Proceedings of COMPSTAT (pp. 177–186). Berlin: Springer.
5. Brockman, G., Cheung, V., Pettersson, L., Schneider, J., Schulman, J., Tang, J., & Zaremba, W. (2016). OpenAI Gym. CoRR arXiv:1606.01540v1.
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