EDITORIAL
Published on 17 Mar 2021
Editorial: Understanding and Bridging the Gap Between Neuromorphic Computing and Machine Learning
doi 10.3389/fncom.2021.665662
- 6,449 views
- 11 citations
- Frontiers in Computational Neuroscience
- Research Topics
- Understanding and Bridging the Gap between Neuromorphic Computing and Machine Learning
Understanding and Bridging the Gap between Neuromorphic Computing and Machine Learning
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Articles
ORIGINAL RESEARCH
Published on 02 Feb 2021
End-to-End Implementation of Various Hybrid Neural Networks on a Cross-Paradigm Neuromorphic Chip
doi 10.3389/fnins.2021.615279
- 3,778 views
- 10 citations
ORIGINAL RESEARCH
Published on 23 Dec 2020
Bitstream-Based Neural Network for Scalable, Efficient, and Accurate Deep Learning Hardware
doi 10.3389/fnins.2020.543472
- 3,082 views
- 5 citations
ORIGINAL RESEARCH
Published on 18 Sep 2020
Exploring Neuromodulation for Dynamic Learning
doi 10.3389/fnins.2020.00928
- 4,469 views
- 8 citations
ORIGINAL RESEARCH
Published on 21 Jul 2020
Bayesian Multi-objective Hyperparameter Optimization for Accurate, Fast, and Efficient Neural Network Accelerator Design
doi 10.3389/fnins.2020.00667
- 7,177 views
- 38 citations
ORIGINAL RESEARCH
Published on 30 Jun 2020
Toward Scalable, Efficient, and Accurate Deep Spiking Neural Networks With Backward Residual Connections, Stochastic Softmax, and Hybridization
doi 10.3389/fnins.2020.00653
- 6,281 views
- 72 citations
ORIGINAL RESEARCH
Published on 24 Jun 2020
Supervised Learning in All FeFET-Based Spiking Neural Network: Opportunities and Challenges
doi 10.3389/fnins.2020.00634
- 10,314 views
- 75 citations
ORIGINAL RESEARCH
Published on 28 May 2020
Neuromorphic Systems Design by Matching Inductive Biases to Hardware Constraints
doi 10.3389/fnins.2020.00437
- 2,400 views
ORIGINAL RESEARCH
Published on 12 May 2020
Synaptic Plasticity Dynamics for Deep Continuous Local Learning (DECOLLE)
doi 10.3389/fnins.2020.00424
- 15,667 views
- 195 citations
ORIGINAL RESEARCH
Published on 05 May 2020
Efficient Processing of Spatio-Temporal Data Streams With Spiking Neural Networks
doi 10.3389/fnins.2020.00439
- 7,882 views
- 73 citations
HYPOTHESIS AND THEORY
Published on 29 Apr 2020
Noise Helps Optimization Escape From Saddle Points in the Synaptic Plasticity
doi 10.3389/fnins.2020.00343
- 3,495 views
- 1 citation
CORRECTION
Published on 15 Apr 2020
Corrigendum: A Curiosity-Based Learning Method for Spiking Neural Networks
doi 10.3389/fncom.2020.00028
- 1,719 views
- 1 citation
Published in
Frontiers in Computational Neuroscience
Participating Journals
Frontiers in Neuroscience
- 3.2 impact factor
- 6.2 citescore
Impact
- 127kTopic views
- 95kArticle views
- 25kArticle downloads