Suhas Kumar

According to our database, Suhas Kumar authored at least 16 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Incorruptible Neural Networks: Training Models that can Generalize to Large Internal Perturbations.

Philip Jacobson, Ben Feinberg, Suhas Kumar, Sapan Agarwal, T. Patrick Xiao, Christopher H. Bennett

CoRR, February, 2026

2025

Ovonic switches enable energy-efficient dendrite-like computing.

Unhyeon Kang, Jaesang Lee, Seungmin Oh, Hanchan Song, Jongkil Park, Jaewook Kim, Seongsik Park, Hyun Jae Jang, Sangbum Kim, Su-In Yi, Suhas Kumar, Suyoun Lee

CoRR, December, 2025

Forward Target Propagation: A Forward-Only Approach to Global Error Credit Assignment via Local Losses.

Nazmus Saadat As-Saquib, A. N. M. Nafiz Abeer, Hung-Ta Chien, Byung-Jun Yoon, Suhas Kumar, Su-In Yi

CoRR, June, 2025

Self-heating electrochemical memory for high-precision analog computing.

Adam L. Gross, Sangheon Oh, François Léonard, Wyatt Hodges, T. Patrick Xiao, Joshua D. Sugar, Jacklyn Zhu, Sritharini Radhakrishnan, Sangyong Lee, Jolie Wang, Adam S. Christensen, Sam Lilak, Patrick S. Finnegan, Patrick Crandall, Christopher H. Bennett, William Wahby, Robin Jacobs-Gedrim, Matthew J. Marinella, Suhas Kumar, Sapan Agarwal, Yiyang Li, A. Alec Talin, Elliot J. Fuller

CoRR, May, 2025

Energy-Efficient Knapsack Optimization Using Probabilistic Memristor Crossbars.

Jinzhan Li, Suhas Kumar, Su-In Yi

Adv. Intell. Syst., 2025

Point cloud processing using non-volatile memories with circuit and sensor noise.

Minseong Park, Su-In Yi, Suhas Kumar

Proceedings of the IEEE International Symposium on Circuits and Systems, 2025

2023

Research Challenges for Energy-Efficient Computing in Automated Vehicles.

Robert P. Dick, Rob Aitken, Jace Mogill, John Paul Strachan, Kirk Bresniker, Wei Lu, Yorie Nakahira, Zhiyong Li, Matthew J. Marinella, William Severa, A. Alec Talin, Craig M. Vineyard, Suhas Kumar, Christian Mailhiot, Lennie Klebanoff

Computer, March, 2023

Energy-based learning algorithms for analog computing: a comparative study.

Benjamin Scellier, Maxence Ernoult, Jack D. Kendall, Suhas Kumar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Combinatorial Optimization in Hopfield Networks with Noise and Diagonal Perturbations.

Su-In Yi, Suhas Kumar, R. Stanley Williams

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

2021

Improved Hopfield Network Optimization Using Manufacturable Three-Terminal Electronic Synapses.

Su-In Yi, Suhas Kumar, R. Stanley Williams

IEEE Trans. Circuits Syst. I Regul. Pap., 2021

2020

A Simplified Model for a NbO2 Mott Memristor Physical Realization.

Ioannis Messaris, Ronald Tetzlaff, Alon Ascoli, R. Stanley Williams, Suhas Kumar, Leon O. Chua

Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

Classical Adiabatic Annealing in Memristor Hopfield Neural Networks for Combinatorial Optimization.

Suhas Kumar, Thomas Van Vaerenbergh, John Paul Strachan

Proceedings of the International Conference on Rebooting Computing, 2020

2019

Thermodynamic Computing.

Tom Conte, Erik DeBenedictis, Natesh Ganesh, Todd Hylton, John Paul Strachan, R. Stanley Williams, Alexander A. Alemi, Lee Altenberg, Gavin E. Crooks, James P. Crutchfield, Lídia del Rio, Josh Deutsch, Michael Robert DeWeese, Khari Douglas, Massimiliano Esposito, Michael P. Frank, Robert Fry, Peter Harsha, Mark D. Hill, Christopher T. Kello, Jeff Krichmar, Suhas Kumar, Shih-Chii Liu, Seth Lloyd, Matteo Marsili, Ilya Nemenman, Alex Nugent, Norman H. Packard, Dana Randall, Peter Sadowski, Narayana Santhanam, Robert Shaw, Adam Z. Stieg, Elan Stopnitzky, Christof Teuscher, Chris Watkins, David H. Wolpert, J. Joshua Yang, Yan Yufik

CoRR, 2019

Harnessing Intrinsic Noise in Memristor Hopfield Neural Networks for Combinatorial Optimization.

Fuxi Cai, Suhas Kumar, Thomas Van Vaerenbergh, Rui Liu, Can Li, Shimeng Yu, Qiangfei Xia, J. Joshua Yang, Raymond G. Beausoleil, Wei Lu, John Paul Strachan

CoRR, 2019

Future Computing Systems (FCS) to Support "Understanding" Capability.

Raymond G. Beausoleil, Thomas Van Vaerenbergh, Kirk Bresniker, Catherine Graves, Kimberly Keeton, Suhas Kumar, Can Li, Dejan S. Milojicic, Sergey Serebryakov, John Paul Strachan

Proceedings of the 2019 IEEE International Conference on Rebooting Computing, 2019

The Art and Science of Constructing a Memristor Model: Updated.

Suhas Kumar, Gary Gibson, Catherine E. Graves, Matthew D. Pickett, John Paul Strachan, R. Stanley Williams

Proceedings of the Handbook of Memristor Networks., 2019