Matthias Plappert

Publications

Journals

OpenAI: M. Andrychowicz, B. Baker, M. Chociej, R. Jozefowicz, B. McGrew, J. Pachocki, A. Petron, M. Plappert, G. Powell, A. Ray, J. Schneider, S. Sidor, J. Tobin, P. Welinder, L. Weng, and W. Zaremba, Learning Dexterous In-Hand Manipulation, The International Journal of Robotics Research (IJRR), Vol. 39(1), pp. 3-20, January 2020 (pre-print August 2018) [pdf, pre-print, blog post, video 1, video 2, bib]
M. Plappert, C. Mandery, and T. Asfour, Learning a bidirectional mapping between human whole-body motion and natural language using deep recurrent neural networks, Robotics and Autonomous Systems, Vol. 109, pp. 13-26, November 2018 [pdf, video, dataset, code, bib]
M. Plappert, C. Mandery, and T. Asfour, The KIT Motion-Language Dataset, Big Data, Vol. 4, No. 4, pp. 236-252, December 2016 [pdf, dataset, code, bib]

Conferences

M. Plappert, R. Houthooft, P. Dhariwal, S. Sidor, R.Y. Chen, X. Chen, T. Asfour, P. Abbeel, and M. Andrychowicz, Parameter Space Noise for Exploration, In the proceedings of the International Conference on Learning Representations (ICLR), Vancouver, Canada, April 2018 [pdf, blog post, code, bib]
C. Mandery, M. Plappert, J. Borràs, and T. Asfour, Dimensionality Reduction for Whole-Body Human Motion Recognition, 19th International Conference on Information Fusion (FUSION), pp. 355-362, July 2016 [pdf, bib]

Pre-Prints & Tech Reports

K. Cobbe, V. Kosaraju, M. Bavarian, M. Chen, H. Jun, L. Kaiser, M. Plappert, J. Tworek, J. Hilton, R. Nakano, C. Hesse, and J. Schulman, Training Verifiers to Solve Math Word Problems, arXiv:2110.14168, October 2021, [pdf, blog post]
M. Chen, J. Tworek, H. Jun, Q. Yuan, H. Ponde de Oliveira Pinto, J. Kaplan, H. Edwards, Y. Burda, N. Joseph, G. Brockman, A. Ray, R. Puri, G. Krueger, M. Petrov, H. Khlaaf, G. Sastry, P. Mishkin, B. Chan, S. Gray, N. Ryder, M. Pavlov, A. Power, L. Kaiser, M. Bavarian, C. Winter, P. Tillet, F. Such, D. Cummings, M. Plappert, F. Chantzis, E. Barnes, A. Herbert-Voss, W.H. Guss, A. Nichol, A. Paino, N. Tezak, J. Tang, I. Babuschkin, S. Balaji, S. Jain, W. Saunders, C. Hesse, A.N. Carr, J. Leike, J. Achiam, V. Misra, E. Morikawa, A. Radford, M. Knight, M. Brundage, M. Murati, K. Mayer, P. Welinder, B. McGrew, D. Amodei, S. McCandlish, I. Sutskever, and W. Zaremba, Evaluating Large Language Models Trained on Code, arXiv:2107.03374, July 2021 [pdf, blog post]
OpenAI: M. Plappert, R. Sampedro, T. Xu, I. Akkaya, V. Kosaraju, P. Welinder, R. D'Sa, A. Petron, H. Ponde de Oliveira Pinto, A. Paino, H. Noh, L. Weng, Q. Yuan, C. Chu, and W. Zaremba, Asymmetric self-play for automatic goal discovery in robotic manipulation, arXiv:2101.04882, January 2021 [pdf, videos]
L. Zhang, M. Plappert, and W. Zaremba, Predicting Sim-to-Real Transfer with Probabilistic Dynamics Models, arXiv:2009.12864, September 2020 [pdf]
OpenAI: I. Akkaya, M. Andrychowicz, M. Chociej, M. Litwin, B. McGrew, A. Petron, A. Paino, M. Plappert, G. Powell, R. Ribas, J. Schneider, N. Tezak, J. Tworek, P. Welinder, L. Weng, Q. Yuan, W. Zaremba, and L. Zhang, Solving Rubik's Cube with a Robot Hand, arXiv:1910.07113, October 2019 [pdf, blog post, all videos, bib]
M. Plappert, M. Andrychowicz, A. Ray, B. McGrew, B. Baker, G. Powell, J. Schneider, J. Tobin, M. Chociej, P. Welinder, V. Kumar, and W. Zaremba, Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research, arXiv:1802.09464, February 2018 [pdf, blog post, code, bib]

Theses

M. Plappert, Parameter Space Noise for Exploration in Deep Reinforcement Learning, Master thesis, November 2017 [pdf, bib]
M. Plappert, Classification of Human Whole-Body Motion using Hidden Markov Models, Bachelor thesis, August 2015 [pdf, code, bib]

Matthias Plappert

Publications

Journals

Conferences

Pre-Prints & Tech Reports

Theses

Talks

Projects

Coverage