{"total":33,"rows":[{"id":"2109.12894","title":"Training Spiking Neural Networks Using Lessons From Deep Learning","created":"2021-09-27","cited_by_count":259,"area":null},{"id":"2203.08147","title":"Energy-Latency Attacks via Sponge Poisoning","created":"2022-03-14","cited_by_count":29,"area":null},{"id":"2305.11252","title":"Brain-inspired learning in artificial neural networks: a review","created":"2023-05-18","cited_by_count":26,"area":null},{"id":"2106.01288","title":"Bottom-up and top-down approaches for the design of neuromorphic processing systems: Tradeoffs and synergies between natural and artificial intelligence","created":"2021-06-02","cited_by_count":21,"area":null},{"id":"2206.06506","title":"Spiking Neural Networks for Frame-based and Event-based Single Object Localization","created":"2022-06-13","cited_by_count":18,"area":null},{"id":"2112.13896","title":"Two Sparsities Are Better Than One: Unlocking the Performance Benefits of Sparse-Sparse Networks","created":"2021-12-27","cited_by_count":15,"area":null},{"id":"2203.06951","title":"Computer Vision and Deep Learning for Fish Classification in Underwater Habitats: A Survey","created":"2022-03-14","cited_by_count":14,"area":null},{"id":"2209.15137","title":"Generalizable machine learning for stress monitoring from wearable devices: A systematic literature review","created":"2022-09-29","cited_by_count":12,"area":null},{"id":"2210.03515","title":"Spiking neural networks for nonlinear regression","created":"2022-10-06","cited_by_count":10,"area":null},{"id":"2306.15749","title":"To Spike or Not To Spike: A Digital Hardware Perspective on Deep Learning Acceleration","created":"2023-06-27","cited_by_count":10,"area":null},{"id":"2406.19230","title":"Spiking Convolutional Neural Networks for Text Classification","created":"2024-06-27","cited_by_count":10,"area":null},{"id":"2201.11915","title":"The fine line between dead neurons and sparsity in binarized spiking neural networks","created":"2022-01-28","cited_by_count":8,"area":null},{"id":"2110.01639","title":"An energy-based model for neuro-symbolic reasoning on knowledge graphs","created":"2021-10-04","cited_by_count":4,"area":null},{"id":"2202.07221","title":"Navigating Local Minima in Quantized Spiking Neural Networks","created":"2022-02-15","cited_by_count":4,"area":null},{"id":"2204.04768","title":"Analysis of Power-Oriented Fault Injection Attacks on Spiking Neural Networks","created":"2022-04-10","cited_by_count":4,"area":null},{"id":"2206.05394","title":"Applications of Deep Learning in Fish Habitat Monitoring: A Tutorial and Survey","created":"2022-06-11","cited_by_count":4,"area":null},{"id":"2310.06488","title":"SpikeCLIP: A Contrastive Language-Image Pretrained Spiking Neural Network","created":"2023-10-10","cited_by_count":4,"area":null},{"id":"2206.09951","title":"Seizure Detection and Prediction by Parallel Memristive Convolutional Neural Networks","created":"2022-06-20","cited_by_count":3,"area":null},{"id":"2211.10725","title":"Intelligence Processing Units Accelerate Neuromorphic Learning","created":"2022-11-19","cited_by_count":3,"area":null},{"id":"2402.06357","title":"The SkipSponge Attack: Sponge Weight Poisoning of Deep Neural Networks","created":"2024-02-09","cited_by_count":3,"area":null},{"id":"2206.12992","title":"Gradient-based Neuromorphic Learning on Dynamical RRAM Arrays","created":"2022-06-26","cited_by_count":2,"area":null},{"id":"2404.19668","title":"SQUAT: Stateful Quantization-Aware Training in Recurrent Spiking Neural Networks","created":"2024-04-15","cited_by_count":2,"area":null},{"id":"2102.07243","title":"Naturalizing Neuromorphic Vision Event Streams Using GANs","created":"2021-02-14","cited_by_count":1,"area":null},{"id":"2106.06749","title":"A decreasing scaling transition scheme from Adam to SGD","created":"2021-06-12","cited_by_count":1,"area":null},{"id":"2201.06703","title":"Design Space Exploration of Dense and Sparse Mapping Schemes for RRAM Architectures","created":"2022-01-18","cited_by_count":1,"area":null},{"id":"2203.01416","title":"A Fully Memristive Spiking Neural Network with Unsupervised Learning","created":"2022-03-02","cited_by_count":1,"area":null},{"id":"2501.08152","title":"Energy Backdoor Attack to Deep Neural Networks","created":"2025-01-14","cited_by_count":1,"area":null},{"id":"2203.01426","title":"SPICEprop: Backpropagating Errors Through Memristive Spiking Neural Networks","created":"2022-03-02","cited_by_count":0,"area":null},{"id":"2311.02110","title":"Feature Attribution Explanations for Spiking Neural Networks","created":"2023-11-02","cited_by_count":0,"area":null},{"id":"2410.04992","title":"MC-QDSNN: Quantized Deep evolutionary SNN with Multi-Dendritic Compartment Neurons for Stress Detection using Physiological Signals","created":"2024-10-07","cited_by_count":0,"area":null},{"id":"2503.13492","title":"Event-Driven Implementation of a Physical Reservoir Computing Framework for superficial EMG-based Gesture Recognition","created":"2025-03-10","cited_by_count":0,"area":null},{"id":"2601.16652","title":"Reliable Brain Tumor Segmentation Based on Spiking Neural Networks with Efficient Training","created":"2026-01-23","cited_by_count":0,"area":null},{"id":"2609.32930","title":"EEG-Based Motor Imagery BCI Algorithms and Technologies: A Review","created":"2026-09-26","cited_by_count":0,"area":null}],"next_cursor":null}