Christopher Grimm

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 18

Top Topics

Neural Network Training

Space Filling Curves

Reinforcement Learning

Exact Computation

Top Venues

IEEE Trans. Circuits Syst. I Regul. Pap.

Publications

Christopher Grimm, Jinseok Lee, Naveen Verma
Training Neural Networks With In-Memory-Computing Hardware and Multi-Level Radix-4 Inputs. IEEE Trans. Circuits Syst. I Regul. Pap. 71 (4) (2024)
Christopher Grimm, Naveen Verma
Neural Network Training on In-Memory-Computing Hardware With Radix-4 Gradients. IEEE Trans. Circuits Syst. I Regul. Pap. 69 (10) (2022)
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. IEEE Trans. Veh. Technol. 71 (9) (2022)
Christopher Grimm, André Barreto, Satinder Singh
Approximate Value Equivalence. NeurIPS (2022)
Christopher Grimm, Naveen Verma
Neural Network Training on In-memory-computing Hardware with Radix-4 Gradients. CoRR (2022)
Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh
Proper Value Equivalence. NeurIPS (2021)
Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh
Proper Value Equivalence. CoRR (2021)
Christopher Grimm, André Barreto, Satinder Singh, David Silver
The Value Equivalence Principle for Model-Based Reinforcement Learning. CoRR (2020)
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 (2020)
Christopher Grimm, André Barreto, Satinder Singh, David Silver
The Value Equivalence Principle for Model-Based Reinforcement Learning. NeurIPS (2020)
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 (2019)
Christopher Grimm, Satinder Singh
Learning Independently-Obtainable Reward Functions. CoRR (2019)
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 (2018)
Melrose Roderick, Christopher Grimm, Stefanie Tellex
Deep Abstract Q-Networks. AAMAS (2018)
Yuhang Song, Christopher Grimm, Xianming Wang, Michael L. Littman
Learning Approximate Stochastic Transition Models. CoRR (2017)
Christopher Grimm, Dilip Arumugam, Siddharth Karamcheti, David Abel, Lawson L. S. Wong, Michael L. Littman
Latent Attention Networks. CoRR (2017)
Melrose Roderick, Christopher Grimm, Stefanie Tellex
Deep Abstract Q-Networks. CoRR (2017)
Christopher Grimm, Yuhang Song, Michael L. Littman
Summable Reparameterizations of Wasserstein Critics in the One-Dimensional Setting. CoRR (2017)