{"total":35,"rows":[{"id":"2110.11417","title":"HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise","created":"2021-10-06","cited_by_count":65,"area":null},{"id":"2201.10355","title":"Neural Architecture Search for Spiking Neural Networks","created":"2022-01-23","cited_by_count":53,"area":null},{"id":"2210.06686","title":"Real Spike: Learning Real-valued Spikes for Spiking Neural Networks","created":"2022-10-13","cited_by_count":22,"area":null},{"id":"2104.12528","title":"Spatio-Temporal Pruning and Quantization for Low-latency Spiking Neural Networks","created":"2021-04-26","cited_by_count":21,"area":null},{"id":"2110.05929","title":"One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latency","created":"2021-10-01","cited_by_count":17,"area":null},{"id":"2303.10276","title":"Unleashing the Potential of Spiking Neural Networks by Dynamic Confidence","created":"2023-03-17","cited_by_count":15,"area":null},{"id":"2209.03358","title":"Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples","created":"2022-09-07","cited_by_count":13,"area":null},{"id":"2406.13672","title":"Q-SNNs: Quantized Spiking Neural Networks","created":"2024-06-19","cited_by_count":12,"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":"2107.12445","title":"Towards Low-Latency Energy-Efficient Deep SNNs via Attention-Guided Compression","created":"2021-07-16","cited_by_count":7,"area":null},{"id":"2206.09449","title":"SNN2ANN: A Fast and Memory-Efficient Training Framework for Spiking Neural Networks","created":"2022-06-19","cited_by_count":7,"area":null},{"id":"2311.09266","title":"Adversarially Robust Spiking Neural Networks Through Conversion","created":"2023-11-15","cited_by_count":7,"area":null},{"id":"2103.00944","title":"A Little Energy Goes a Long Way: Build an Energy-Efficient, Accurate Spiking Neural Network from Convolutional Neural Network","created":"2021-03-01","cited_by_count":5,"area":null},{"id":"2307.14464","title":"Single Channel Speech Enhancement Using U-Net Spiking Neural Networks","created":"2023-07-26","cited_by_count":5,"area":null},{"id":"2502.14344","title":"Towards Accurate Binary Spiking Neural Networks: Learning with Adaptive Gradient Modulation Mechanism","created":"2025-02-20","cited_by_count":5,"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":"2203.01158","title":"Rethinking Pretraining as a Bridge from ANNs to SNNs","created":"2022-03-02","cited_by_count":4,"area":null},{"id":"2405.02543","title":"Exploring Extreme Quantization in Spiking Language Models","created":"2024-05-04","cited_by_count":4,"area":null},{"id":"2104.05124","title":"A Bop and Beyond: A Second Order Optimizer for Binarized Neural Networks","created":"2021-04-11","cited_by_count":3,"area":null},{"id":"2107.11979","title":"HYPER-SNN: Towards Energy-efficient Quantized Deep Spiking Neural Networks for Hyperspectral Image Classification","created":"2021-07-26","cited_by_count":3,"area":null},{"id":"2304.10749","title":"Multi-scale Evolutionary Neural Architecture Search for Deep Spiking Neural Networks","created":"2023-04-21","cited_by_count":3,"area":null},{"id":"2308.04672","title":"Resource Constrained Model Compression via Minimax Optimization for Spiking Neural Networks","created":"2023-08-09","cited_by_count":3,"area":null},{"id":"2307.04054","title":"Deep Unsupervised Learning Using Spike-Timing-Dependent Plasticity","created":"2023-07-08","cited_by_count":2,"area":null},{"id":"2402.01782","title":"Benchmarking Spiking Neural Network Learning Methods with Varying Locality","created":"2024-02-01","cited_by_count":2,"area":null},{"id":"2403.18609","title":"A survey on learning models of spiking neural membrane systems and spiking neural networks","created":"2024-03-27","cited_by_count":2,"area":null},{"id":"2405.00699","title":"Direct Training Needs Regularisation: Anytime Optimal Inference Spiking Neural Network","created":"2024-04-15","cited_by_count":2,"area":null},{"id":"2511.12502","title":"BSO: Binary Spiking Online Optimization Algorithm","created":"2025-11-16","cited_by_count":2,"area":null},{"id":"2201.10879","title":"S$^3$NN: Time Step Reduction of Spiking Surrogate Gradients for Training Energy Efficient Single-Step Spiking Neural Networks","created":"2022-01-26","cited_by_count":1,"area":null},{"id":"2309.05263","title":"Brain-inspired Evolutionary Architectures for Spiking Neural Networks","created":"2023-09-11","cited_by_count":1,"area":null},{"id":"2409.15849","title":"Twin Network Augmentation: A Novel Training Strategy for Improved Spiking Neural Networks and Efficient Weight Quantization","created":"2024-09-24","cited_by_count":1,"area":null},{"id":"2503.16775","title":"Region Masking to Accelerate Video Processing on Neuromorphic Hardware","created":"2025-03-21","cited_by_count":1,"area":null},{"id":"2604.27007","title":"Binary Spiking Neural Networks as Causal Models","created":"2026-04-29","cited_by_count":1,"area":null},{"id":"2307.04356","title":"InfLoR-SNN: Reducing Information Loss for Spiking Neural Networks","created":"2023-07-10","cited_by_count":0,"area":null},{"id":"2505.15833","title":"Adversarially Robust Spiking Neural Networks with Sparse Connectivity","created":"2025-05-16","cited_by_count":0,"area":null},{"id":"2508.12609","title":"A Self-Ensemble Inspired Approach for Effective Training of Binary-Weight Spiking Neural Networks","created":"2025-08-18","cited_by_count":0,"area":null}],"next_cursor":null}