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CMOS-compatible Ising and Potts annealing using single-photon avalanche diodes
Nature Electronics,
2023
DOI:10.1038/s41928-023-01065-0
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[2]
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A highly parameterizable framework for Conditional Restricted Boltzmann Machine based workloads accelerated with FPGAs and OpenCL
Future Generation Computer Systems,
2020
DOI:10.1016/j.future.2019.10.025
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Integrated analog neurons inspired by mimicking synapses with metal-oxide memristive devices
Japanese Journal of Applied Physics,
2020
DOI:10.35848/1347-4065/ab8164
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An Energy-efficient Multi-core Restricted Boltzmann Machine Processor with On-chip Bio-plausible Learning and Reconfigurable Sparsity
2020 IEEE Asian Solid-State Circuits Conference (A-SSCC),
2020
DOI:10.1109/A-SSCC48613.2020.9336135
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A shared synapse architecture for efficient FPGA implementation of autoencoders
PLOS ONE,
2018
DOI:10.1371/journal.pone.0194049
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Artificial neuron operations and spike-timing-dependent plasticity using memristive devices for brain-inspired computing
Japanese Journal of Applied Physics,
2018
DOI:10.7567/JJAP.57.04FK06
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[7]
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Proposal, analysis and demonstration of Analog/Digital-mixed Neural Networks based on memristive device arrays
2018 IEEE International Symposium on Circuits and Systems (ISCAS),
2018
DOI:10.1109/ISCAS.2018.8351298
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The Optimization of Parallel Convolutional RBM Based on Spark
International Journal of Wavelets, Multiresolution and Information Processing,
2018
DOI:10.1142/S0219691319400113
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Hardware Artificial Intelligence Driven by Interdisciplinary Fusion of Information Science, Neuroscience and Manufacturing
The Brain & Neural Networks,
2018
DOI:10.3902/jnns.25.148
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Reducing calculation requirements in FPGA implementation of deep learning algorithms for online anomaly intrusion detection
2017 IEEE National Aerospace and Electronics Conference (NAECON),
2017
DOI:10.1109/NAECON.2017.8268745
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[11]
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Live demonstration: Feature extraction system using restricted Boltzmann machines on FPGA
2017 IEEE International Symposium on Circuits and Systems (ISCAS),
2017
DOI:10.1109/ISCAS.2017.8050402
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