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Christopher Grimm
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2020 – today
- 2024
- [j3]Christopher Grimm
, Jinseok Lee
Training Neural Networks With In-Memory-Computing Hardware and Multi-Level Radix-4 Inputs. IEEE Trans. Circuits Syst. I Regul. Pap. 71(4): 1781-1793 (2024) - 2022
- [j2]Christopher Grimm
Neural Network Training on In-Memory-Computing Hardware With Radix-4 Gradients. IEEE Trans. Circuits Syst. I Regul. Pap. 69(10): 4056-4068 (2022) - [j1]Christopher Grimm
Warping of Radar Data Into Camera Image for Cross-Modal Supervision in Automotive Applications. IEEE Trans. Veh. Technol. 71(9): 9435-9449 (2022) - [c4]Christopher Grimm, André Barreto, Satinder Singh:
Approximate Value Equivalence. NeurIPS 2022 - [i11]Christopher Grimm, Naveen Verma:
Neural Network Training on In-memory-computing Hardware with Radix-4 Gradients. CoRR abs/2203.04821 (2022) - 2021
- [c3]Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh:
Proper Value Equivalence. NeurIPS 2021: 7773-7786 - [i10]Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh:
Proper Value Equivalence. CoRR abs/2106.10316 (2021) - 2020
- [c2]Christopher Grimm, André Barreto, Satinder Singh, David Silver:
The Value Equivalence Principle for Model-Based Reinforcement Learning. NeurIPS 2020 - [i9]Christopher Grimm, André Barreto, Satinder Singh, David Silver:
The Value Equivalence Principle for Model-Based Reinforcement Learning. CoRR abs/2011.03506 (2020) - [i8]Christopher Grimm, Tai Fei, Ernst Warsitz, Ridha Farhoud, Tobias Breddermann, Reinhold Haeb-Umbach:
Warping of Radar Data into Camera Image for Cross-Modal Supervision in Automotive Applications. CoRR abs/2012.12809 (2020)
2010 – 2019
- 2019
- [i7]Christopher Grimm, Satinder Singh:
Learning Independently-Obtainable Reward Functions. CoRR abs/1901.08649 (2019) - [i6]Christopher Grimm, Irina Higgins, André Barreto, Denis Teplyashin, Markus Wulfmeier, Tim Hertweck, Raia Hadsell, Satinder Singh:
Disentangled Cumulants Help Successor Representations Transfer to New Tasks. CoRR abs/1911.10866 (2019) - 2018
- [c1]Melrose Roderick, Christopher Grimm, Stefanie Tellex:
Deep Abstract Q-Networks. AAMAS 2018: 131-138 - [i5]Dilip Arumugam, David Abel, Kavosh Asadi, Nakul Gopalan, Christopher Grimm, Jun Ki Lee, Lucas Lehnert, Michael L. Littman:
Mitigating Planner Overfitting in Model-Based Reinforcement Learning. CoRR abs/1812.01129 (2018) - 2017
- [i4]Christopher Grimm, Dilip Arumugam, Siddharth Karamcheti, David Abel, Lawson L. S. Wong, Michael L. Littman:
Latent Attention Networks. CoRR abs/1706.00536 (2017) - [i3]Christopher Grimm, Yuhang Song, Michael L. Littman:
Summable Reparameterizations of Wasserstein Critics in the One-Dimensional Setting. CoRR abs/1709.06533 (2017) - [i2]Melrose Roderick, Christopher Grimm, Stefanie Tellex:
Deep Abstract Q-Networks. CoRR abs/1710.00459 (2017) - [i1]Yuhang Song, Christopher Grimm, Xianming Wang, Michael L. Littman:
Learning Approximate Stochastic Transition Models. CoRR abs/1710.09718 (2017)
Coauthor Index
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