Christopher H. Bennett
Orcid: 0000-0002-6989-292X
According to our database1,
Christopher H. Bennett
authored at least 33 papers
between 2015 and 2023.
Collaborative distances:
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Bibliography
2023
Neuromorph. Comput. Eng., June, 2023
Enabling High-Speed, High-Resolution Space-based Focal Plane Arrays with Analog In-Memory Computing.
Proceedings of the 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), 2023
Proceedings of the IEEE International Reliability Physics Symposium, 2023
Proceedings of the IEEE International Conference on Rebooting Computing, 2023
2022
An Accurate, Error-Tolerant, and Energy-Efficient Neural Network Inference Engine Based on SONOS Analog Memory.
IEEE Trans. Circuits Syst. I Regul. Pap., 2022
An out-of-distribution discriminator based on Bayesian neural network epistemic uncertainty.
CoRR, 2022
Intrinsic Lateral Inhibition Facilitates Winner-Take-All in Domain Wall Racetrack Arrays for Neuromorphic Computing.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2022
Proceedings of the IEEE International Symposium on Circuits and Systems, 2022
Proceedings of the IEEE International Conference on Rebooting Computing, 2022
2021
Shape-Dependent Multi-Weight Magnetic Artificial Synapses for Neuromorphic Computing.
CoRR, 2021
CoRR, 2021
Controllable reset behavior in domain wall-magnetic tunnel junction artificial neurons for task-adaptable computation.
CoRR, 2021
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2021
2020
Domain Wall Leaky Integrate-and-Fire Neurons with Shape-Based Configurable Activation Functions.
CoRR, 2020
Unsupervised Competitive Hardware Learning Rule for Spintronic Clustering Architecture.
CoRR, 2020
Evaluating complexity and resilience trade-offs in emerging memory inference machines.
Proceedings of the NICE '20: Neuro-inspired Computational Elements Workshop, 2020
Proceedings of the IEEE International Symposium on Circuits and Systems, 2020
CMOS-Free Magnetic Domain Wall Leaky Integrate-and-Fire Neurons with Intrinsic Lateral Inhibition.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2020
Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2020
Proceedings of the 2020 IEEE International Reliability Physics Symposium, 2020
2019
Shape-based Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron.
CoRR, 2019
Contrasting Advantages of Learning With Random Weights and Backpropagation in Non-Volatile Memory Neural Networks.
IEEE Access, 2019
Wafer-Scale TaOx Device Variability and Implications for Neuromorphic Computing Applications.
Proceedings of the IEEE International Reliability Physics Symposium, 2019
2018
Local learning with highly analog memory devices. (Apprentissage local avec des dispositifs de mémoire hautement analogiques).
PhD thesis, 2018
Multiscaled Simulation Methodology for Neuro-Inspired Circuits Demonstrated with an Organic Memristor.
IEEE Trans. Multi Scale Comput. Syst., 2018
2017
Proceedings of the IEEE/ACM International Symposium on Nanoscale Architectures, 2017
2016
Exploiting the Short-term to Long-term Plasticity Transition in Memristive Nanodevice Learning Architectures.
CoRR, 2016
Exploiting the short-term to long-term plasticity transition in memristive nanodevice learning architectures.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
Proceedings of the IEEE International Conference on Rebooting Computing, 2016
2015
Supervised learning with organic memristor devices and prospects for neural crossbar arrays.
Proceedings of the 2015 IEEE/ACM International Symposium on Nanoscale Architectures, 2015