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2020 – today
- 2024
[c6]Catherine D. Schuman, Charles P. Rizzo, Garrett S. Rose, James S. Plank:
Embracing the Hairball: An Investigation of Recurrence in Spiking Neural Networks for Control. NICE 2024: 1-5- [i4]Charles P. Rizzo
, Catherine D. Schuman, James S. Plank:
Speed-based Filtration and DBSCAN of Event-based Camera Data with Neuromorphic Computing. CoRR abs/2401.15212 (2024) - [i3]Charles P. Rizzo, James S. Plank:
A Neuromorphic Implementation of the DBSCAN Algorithm. CoRR abs/2409.14298 (2024) - 2023
- [j1]Hritom Das, Rocco D. Febbo, Charles P. Rizzo, Nishith N. Chakraborty, James S. Plank, Garrett S. Rose:
Optimizations for a Current-Controlled Memristor- Based Neuromorphic Synapse Design. IEEE J. Emerg. Sel. Topics Circuits Syst. 13(4): 889-900 (2023) - [c5]Charles Rizzo, Luke Mccombs, Braxton Haynie, Catherine D. Schuman, James S. Plank:
DVSGesture Recognition with Neuromorphic Observation Space Reduction Techniques. ICONS 2023: 10:1-10:8 - [c4]Charles Rizzo, Catherine D. Schuman, James S. Plank:
Neuromorphic Downsampling of Event-Based Camera Output. NICE 2023: 26-34 - [i2]Hritom Das, Rocco D. Febbo, Charles Rizzo, Nishith N. Chakraborty, James S. Plank, Garrett S. Rose:
Optimizations for a Current-Controlled Memristor-based Neuromorphic Synapse Design. CoRR abs/2305.16418 (2023) - 2022
- [c3]Adam Z. Foshie, Charles Rizzo, Hritom Das, Chaohui Zheng, James S. Plank, Garrett S. Rose:
Benchmark Comparisons of Spike-based Reconfigurable Neuroprocessor Architectures for Control Applications. ACM Great Lakes Symposium on VLSI 2022: 383-386 - [c2]Catherine D. Schuman, Charles Rizzo, John McDonald-Carmack, Nicholas D. Skuda, James S. Plank:
Evaluating Encoding and Decoding Approaches for Spiking Neuromorphic Systems. ICONS 2022: 2:1-2:9 - [c1]Charles Rizzo, Catherine D. Schuman, James S. Plank:
Event-Based Camera Simulation Wrapper for Arcade Learning Environment. ICONS 2022: 24:1-24:5 - [i1]James S. Plank, Chaohui Zheng, Bryson Gullett, Nicholas D. Skuda, Charles Rizzo, Catherine D. Schuman, Garrett S. Rose:
The Case for RISP: A Reduced Instruction Spiking Processor. CoRR abs/2206.14016 (2022)
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