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Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles.
Spinnaker 2: A 10 million core processor system for brain simulation and machine learning (2019)
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An efficient spiking neural network for recognizing gestures with a dvs camera on the loihi neuromorphic processor (2021)
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Converting static image datasets to spiking neuromorphic datasets using saccades
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Closed-loop neuromorphic benchmarks
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Dai, W., Dai, C., Qu, S., Li, J. & Das, S · 2016
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A survey of neuromorphic computing and neural networks in hardware (2017)
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A historical survey of algorithms and hardware architectures for neural-inspired and neuromorphic computing applications
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A low power, fully event-based gesture recognition system
Amir, A. et al · 2017
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Nonhuman primate reaching with multichannel sensorimotor cortex electrophysiology, DOI: https://doi.org/10.5281/zenodo.788569 (2017)
O’Doherty, J. E., Cardoso, M. M. B., Makin, J. G. & Sabes, P. N · 2017
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Prototypical networks for few-shot learning
Snell, J., Swersky, K. & Zemel, R · 2017
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Randomness in neural networks: an overview
Scardapane, S. & Wang, D · 2017
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Large-scale neuromorphic spiking array processors: A quest to mimic the brain
Thakur, C. S. et al · 2018
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Speech commands: A dataset for limited-vocabulary speech recognition
Warden, P · 2018
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Squeeze-and-excitation networks
Hu, J., Shen, L. & Sun, G · 2018
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Loihi: A neuromorphic manycore processor with on-chip learning
Davies, M. et al · 2018
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D-Wave Samplers software package (2018)
D-Wave Systems Inc · 2018
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spynnaker: A software package for running pynn simulations on spinnaker
Rhodes, O. et al · 2018
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Superior arm-movement decoding from cortex with a new, unsupervised-learning algorithm
Makin, J. G., O’Doherty, J. E., Cardoso, M. M. B. & Sabes, P · 2018
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Efficiently and easily integrating differential equations with JiTCODE, JiTCDDE, and JiTCSDE
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Benchmarks for progress in neuromorphic computing
Davies, M · 2019
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Pytorch: An imperative style, high-performance deep learning library
Paszke, A. et al · 2019
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Composing neural algorithms with fugu
Aimone, J. B., Severa, W. & Vineyard, C. M · 2019
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Benchmarking keyword spotting efficiency on neuromorphic hardware
Blouw, P., Choo, X., Hunsberger, E. & Eliasmith, C · 2019
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Rockpool documentaton, DOI: 10.5281/zenodo.3773845 (2019)
Muir, D., Bauer, F. & Weidel, P · 2019
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Mlperf inference benchmark
Reddi, V. J. et al · 2020
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Mlperf training benchmark
Human activity recognition: suitability of a neuromorphic approach for on-edge aiot applications
Fra, V. et al · 2022
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A surrogate gradient spiking baseline for speech command recognition
Bittar, A. & Garner, P. N · 2022
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Real-time brain-machine interface in non-human primates achieves high-velocity prosthetic finger movements using a shallow feedforward neural network decoder
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Progress in mathematical programming solvers from 2001 to 2020
Koch, T., Berthold, T., Pedersen, J. & Vanaret, C · 2022
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A review of non-cognitive applications for neuromorphic computing
Aimone, J. B. et al · 2022
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Spike-inspired rank coding for fast and accurate recurrent neural networks
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Mattson, P. et al · 2020
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Learning to detect objects with a 1 megapixel event camera
Perot, E., de Tournemire, P., Nitti, D., Masci, J. & Sironi, A · 2020
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Few-shot class-incremental learning
Tao, X. et al · 2020
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Learning dynamical systems in noise using convolutional neural networks
Mukhopadhyay, S. & Banerjee, S · 2020
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The m4 competition: 100,000 time series and 61 forecasting methods
Makridakis, S., Spiliotis, E. & Assimakopoulos, V · 2020
Cited alongside, same era.
Spikingjelly
Fang, W. et al · 2020
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Jeffares, A., Guo, Q., Stenetorp, P. & Moraitis, T · 2022
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Bottom-up and top-down approaches for the design of neuromorphic processing systems: Tradeoffs and synergies between natural and artificial intelligence
Frenkel, C., Bol, D. & Indiveri, G · 2023
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Training spiking neural networks using lessons from deep learning
Eshraghian, J. K. et al · 2023
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Model scale versus domain knowledge in statistical forecasting of chaotic systems (2023)
Gilpin, W · 2023
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An analytical estimation of spiking neural networks energy efficiency
Lemaire, E. et al · 2023
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Speech2spikes: Efficient audio encoding pipeline for real-time neuromorphic systems
Stewart, K. M., Shea, T., Pacik-Nelson, N., Gallo, E. & Danielescu, A · 2023
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https://www.synsense.ai/products/speck/
Speck · 2023
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www.innatera.com/snp.pdf
Innatera’s Spiking Neural Processor (SNP) · 2023
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Innatera’s Spiking Neural Processor - brain-like architecture targets ultra-low power ai
Levy, M · 2023
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Mlperf inference policies
MLCommons · 2023
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Green500 · 2023
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MLCommons · 2023
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Synsense xylo · 2023
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Edge impulse: An mlops platform for tiny machine learning (2023)
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Micro-power spoken keyword spotting on xylo audio 2 (2024)
Bos, H. & Muir, D. R · 2024
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Efficient video and audio processing with loihi 2
Shrestha, S. B., Timcheck, J., Frady, P., Campos-Macias, L. & Davies, M · 2024
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On-off neuromorphic ising machines using fowler-nordheim annealers (2024)
Chen, Z. et al · 2024
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Solving qubo on the loihi 2 neuromorphic processor (2024)
Pierro, A. et al · 2024
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Industry applications of neutral-atom quantum computing solving independent set problems (2024)
Wurtz, J. et al · 2024
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Neurobench: Dcase 2020 acoustic scene classification benchmark on xyloaudio 2 (2024)
Ke, W., Khoei, M. & Muir, D · 2024
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Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing
Pedersen, J. E. et al · 2024
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