{"total":170,"rows":[{"id":"2212.05598","title":"Recurrent Vision Transformers for Object Detection with Event Cameras","created":"2022-12-11","cited_by_count":159,"area":null},{"id":"2103.12593","title":"Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks","created":"2021-03-12","cited_by_count":115,"area":null},{"id":"2106.01862","title":"Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks","created":"2021-06-03","cited_by_count":99,"area":null},{"id":"2107.12979","title":"Predictive Coding: a Theoretical and Experimental Review","created":"2021-07-27","cited_by_count":77,"area":null},{"id":"2210.04195","title":"Online Training Through Time for Spiking Neural Networks","created":"2022-10-09","cited_by_count":49,"area":null},{"id":"2305.19868","title":"Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANN","created":"2023-05-31","cited_by_count":46,"area":null},{"id":"2209.00530","title":"Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations","created":"2022-09-01","cited_by_count":42,"area":null},{"id":"2302.02091","title":"Reducing ANN-SNN Conversion Error through Residual Membrane Potential","created":"2023-02-04","cited_by_count":40,"area":null},{"id":"2302.10685","title":"Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes","created":"2023-02-21","cited_by_count":40,"area":null},{"id":"2302.14311","title":"Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks","created":"2023-02-28","cited_by_count":37,"area":null},{"id":"2310.06232","title":"Spiking PointNet: Spiking Neural Networks for Point Clouds","created":"2023-10-10","cited_by_count":34,"area":null},{"id":"2107.03992","title":"A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware","created":"2021-07-08","cited_by_count":32,"area":null},{"id":"2305.19725","title":"Direct Learning-Based Deep Spiking Neural Networks: A Review","created":"2023-05-31","cited_by_count":31,"area":null},{"id":"2105.06562","title":"SpikeMS: Deep Spiking Neural Network for Motion Segmentation","created":"2021-05-13","cited_by_count":29,"area":null},{"id":"2308.06787","title":"RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks","created":"2023-08-13","cited_by_count":28,"area":null},{"id":"2109.01905","title":"Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning","created":"2021-09-04","cited_by_count":27,"area":null},{"id":"2206.06178","title":"Efficient recurrent architectures through activity sparsity and sparse back-propagation through time","created":"2022-06-13","cited_by_count":26,"area":null},{"id":"2103.09985","title":"A deep learning theory for neural networks grounded in physics","created":"2021-03-18","cited_by_count":23,"area":null},{"id":"2110.00375","title":"Fully Spiking Variational Autoencoder","created":"2021-09-26","cited_by_count":22,"area":null},{"id":"2112.03423","title":"Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision","created":"2021-12-06","cited_by_count":22,"area":null},{"id":"2306.08744","title":"High-performance deep spiking neural networks with 0.3 spikes per neuron","created":"2023-06-14","cited_by_count":22,"area":null},{"id":"2505.05522","title":"Continuous Thought Machines","created":"2025-05-08","cited_by_count":22,"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":"2106.07030","title":"The Backpropagation Algorithm Implemented on Spiking Neuromorphic Hardware","created":"2021-06-13","cited_by_count":19,"area":null},{"id":"2305.16044","title":"Exploiting Noise as a Resource for Computation and Learning in Spiking Neural Networks","created":"2023-05-25","cited_by_count":18,"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":"2106.01177","title":"Learning to Time-Decode in Spiking Neural Networks Through the Information Bottleneck","created":"2021-06-02","cited_by_count":15,"area":null},{"id":"2210.01244","title":"Event-based Temporally Dense Optical Flow Estimation with Sequential Learning","created":"2022-10-03","cited_by_count":15,"area":null},{"id":"2104.01677","title":"A contrastive rule for meta-learning","created":"2021-04-04","cited_by_count":14,"area":null},{"id":"2205.02367","title":"Time-multiplexed Neural Holography: A flexible framework for holographic near-eye displays with fast heavily-quantized spatial light modulators","created":"2022-05-05","cited_by_count":14,"area":null},{"id":"2212.01232","title":"Loss shaping enhances exact gradient learning with Eventprop in spiking neural networks","created":"2022-12-02","cited_by_count":14,"area":null},{"id":"2401.04486","title":"Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks","created":"2024-01-09","cited_by_count":14,"area":null},{"id":"2208.13723","title":"Bayesian Continual Learning via Spiking Neural Networks","created":"2022-08-29","cited_by_count":13,"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":"2212.12522","title":"An Exact Mapping From ReLU Networks to Spiking Neural Networks","created":"2022-12-23","cited_by_count":12,"area":null},{"id":"2201.10777","title":"Meta-learning Spiking Neural Networks with Surrogate Gradient Descent","created":"2022-01-26","cited_by_count":10,"area":null},{"id":"2204.07050","title":"Recent Advances and New Frontiers in Spiking Neural Networks","created":"2022-03-12","cited_by_count":10,"area":null},{"id":"2210.03515","title":"Spiking neural networks for nonlinear regression","created":"2022-10-06","cited_by_count":10,"area":null},{"id":"2212.05236","title":"Neuromorphic Computing and Sensing in Space","created":"2022-12-10","cited_by_count":10,"area":null},{"id":"2104.13398","title":"SpikE: spike-based embeddings for multi-relational graph data","created":"2021-04-27","cited_by_count":9,"area":null},{"id":"2304.11857","title":"Accurate and Efficient Event-based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Network","created":"2023-04-24","cited_by_count":9,"area":null},{"id":"2404.19165","title":"DelGrad: Exact event-based gradients for training delays and weights on spiking neuromorphic hardware","created":"2024-04-30","cited_by_count":9,"area":null},{"id":"2405.14398","title":"SpGesture: Source-Free Domain-adaptive sEMG-based Gesture Recognition with Jaccard Attentive Spiking Neural Network","created":"2024-05-23","cited_by_count":9,"area":null},{"id":"2303.10780","title":"A Comprehensive Review of Spiking Neural Networks: Interpretation, Optimization, Efficiency, and Best Practices","created":"2023-03-19","cited_by_count":8,"area":null},{"id":"2304.05422","title":"Differentiable graph-structured models for inverse design of lattice materials","created":"2023-04-11","cited_by_count":8,"area":null},{"id":"2307.16235","title":"Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey","created":"2023-07-30","cited_by_count":8,"area":null},{"id":"2402.11984","title":"Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks","created":"2024-02-19","cited_by_count":8,"area":null},{"id":"2410.11488","title":"Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation","created":"2024-10-15","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":"2306.12465","title":"Efficient Deep Spiking Multi-Layer Perceptrons with Multiplication-Free Inference","created":"2023-06-21","cited_by_count":7,"area":null},{"id":"2409.02111","title":"Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions","created":"2024-08-19","cited_by_count":7,"area":null},{"id":"2108.04521","title":"Multi-domain Collaborative Feature Representation for Robust Visual Object Tracking","created":"2021-08-10","cited_by_count":6,"area":null},{"id":"2108.13621","title":"Spike time displacement based error backpropagation in convolutional spiking neural networks","created":"2021-08-31","cited_by_count":6,"area":null},{"id":"2203.01544","title":"Rethinking the role of normalization and residual blocks for spiking neural networks","created":"2022-03-03","cited_by_count":6,"area":null},{"id":"2304.05440","title":"PixelRNN: In-pixel Recurrent Neural Networks for End-to-end-optimized Perception with Neural Sensors","created":"2023-04-11","cited_by_count":6,"area":null},{"id":"2311.09267","title":"Neuroscience inspired scientific machine learning (Part-1): Variable spiking neuron for regression","created":"2023-11-15","cited_by_count":6,"area":null},{"id":"2312.17216","title":"SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks","created":"2023-12-28","cited_by_count":6,"area":null},{"id":"2104.00165","title":"Encoding Event-Based Data With a Hybrid SNN Guided Variational Auto-encoder in Neuromorphic Hardware","created":"2021-03-31","cited_by_count":5,"area":null},{"id":"2303.11860","title":"Online Transformers with Spiking Neurons for Fast Prosthetic Hand Control","created":"2023-03-21","cited_by_count":5,"area":null},{"id":"2307.12900","title":"Automotive Object Detection via Learning Sparse Events by Spiking Neurons","created":"2023-07-24","cited_by_count":5,"area":null},{"id":"2308.02194","title":"Paired Competing Neurons Improving STDP Supervised Local Learning In Spiking Neural Networks","created":"2023-08-04","cited_by_count":5,"area":null},{"id":"2403.18388","title":"FTBC: Forward Temporal Bias Correction for Optimizing ANN-SNN Conversion","created":"2024-03-27","cited_by_count":5,"area":null},{"id":"2502.20411","title":"Backpropagation-free Spiking Neural Networks with the Forward-Forward Algorithm","created":"2025-02-19","cited_by_count":5,"area":null},{"id":"2109.12813","title":"An optimised deep spiking neural network architecture without gradients","created":"2021-09-27","cited_by_count":4,"area":null},{"id":"2205.09140","title":"Relational representation learning with spike trains","created":"2022-05-18","cited_by_count":4,"area":null},{"id":"2205.10242","title":"EXODUS: Stable and Efficient Training of Spiking Neural Networks","created":"2022-05-20","cited_by_count":4,"area":null},{"id":"2303.12167","title":"Gradient-descent hardware-aware training and deployment for mixed-signal Neuromorphic processors","created":"2023-03-14","cited_by_count":4,"area":null},{"id":"2306.12045","title":"Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes","created":"2023-06-21","cited_by_count":4,"area":null},{"id":"2311.11390","title":"Addressing the speed-accuracy simulation trade-off for adaptive spiking neurons","created":"2023-11-19","cited_by_count":4,"area":null},{"id":"2105.05609","title":"Deep Spiking Convolutional Neural Network for Single Object Localization Based On Deep Continuous Local Learning","created":"2021-05-12","cited_by_count":3,"area":null},{"id":"2111.13188","title":"BioLeaF: A Bio-plausible Learning Framework for Training of Spiking Neural Networks","created":"2021-11-14","cited_by_count":3,"area":null},{"id":"2202.00282","title":"Stabilizing Spiking Neuron Training","created":"2022-02-01","cited_by_count":3,"area":null},{"id":"2206.00823","title":"Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules","created":"2022-06-02","cited_by_count":3,"area":null},{"id":"2211.04756","title":"Spiking Neural Network Decision Feedback Equalization","created":"2022-11-09","cited_by_count":3,"area":null},{"id":"2212.01187","title":"Surrogate Gradient Spiking Neural Networks as Encoders for Large Vocabulary Continuous Speech Recognition","created":"2022-12-01","cited_by_count":3,"area":null},{"id":"2307.13007","title":"Sparse-firing regularization methods for spiking neural networks with time-to-first spike coding","created":"2023-07-24","cited_by_count":3,"area":null},{"id":"2411.03022","title":"Flashy Backdoor: Real-world Environment Backdoor Attack on SNNs with DVS Cameras","created":"2024-11-05","cited_by_count":3,"area":null},{"id":"2412.09379","title":"Hybrid variable spiking graph neural networks for energy-efficient scientific machine learning","created":"2024-12-12","cited_by_count":3,"area":null},{"id":"2412.11810","title":"Optimal Gradient Checkpointing for Sparse and Recurrent Architectures using Off-Chip Memory","created":"2024-12-16","cited_by_count":3,"area":null},{"id":"2507.16043","title":"Beyond Rate Coding: Surrogate Gradients Enable Spike Timing Learning in Spiking Neural Networks","created":"2025-07-21","cited_by_count":3,"area":null},{"id":"2109.11045","title":"Training Deep Spiking Auto-encoders without Bursting or Dying Neurons through Regularization","created":"2021-09-22","cited_by_count":2,"area":null},{"id":"2208.02576","title":"Neuro-symbolic computing with spiking neural networks","created":"2022-08-04","cited_by_count":2,"area":null},{"id":"2211.05453","title":"A noise based novel strategy for faster SNN training","created":"2022-11-10","cited_by_count":2,"area":null},{"id":"2311.16151","title":"Estimating Post-Synaptic Effects for Online Training of Feed-Forward SNNs","created":"2023-11-07","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":"2402.18994","title":"Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networks","created":"2024-02-29","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":"2405.13976","title":"EchoSpike Predictive Plasticity: An Online Local Learning Rule for Spiking Neural Networks","created":"2024-05-22","cited_by_count":2,"area":null},{"id":"2407.00957","title":"Expressivity of Neural Networks with Random Weights and Learned Biases","created":"2024-07-01","cited_by_count":2,"area":null},{"id":"2407.04578","title":"Resource-Efficient Speech Quality Prediction through Quantization Aware Training and Binary Activation Maps","created":"2024-07-05","cited_by_count":2,"area":null},{"id":"2504.14015","title":"Causal pieces: analysing and improving spiking neural networks piece by piece","created":"2025-04-18","cited_by_count":2,"area":null},{"id":"2510.27379","title":"Spiking Neural Networks: The Future of Brain-Inspired Computing","created":"2025-10-31","cited_by_count":2,"area":null},{"id":"2511.12199","title":"MPD-SGR: Robust Spiking Neural Networks with Membrane Potential Distribution-Driven Surrogate Gradient Regularization","created":"2025-11-15","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":"2512.09592","title":"CS3D: An Efficient Facial Expression Recognition via Event Vision","created":"2025-12-10","cited_by_count":2,"area":null},{"id":"2601.00245","title":"Modern Neuromorphic AI: From Intra-Token to Inter-Token Processing","created":"2026-01-01","cited_by_count":2,"area":null},{"id":"2106.07854","title":"Population-coding and Dynamic-neurons improved Spiking Actor Network for Reinforcement Learning","created":"2021-06-15","cited_by_count":1,"area":null},{"id":"2201.07602","title":"Including STDP to eligibility propagation in multi-layer recurrent spiking neural networks","created":"2022-01-05","cited_by_count":1,"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":"2203.13207","title":"Supervised Training of Siamese Spiking Neural Networks with Earth Mover's Distance","created":"2022-02-20","cited_by_count":1,"area":null}],"next_cursor":"100"}