Overview

Neuromorphic computing studies algorithms and physical systems that compute through neuron-like dynamics, spikes, sparse events, and sometimes sensing integrated with processing. Common approaches include spiking neural networks trained with surrogate gradients or converted from conventional networks, local learning such as spike-timing-dependent plasticity, reservoir computing, and specialized CMOS, FPGA, memristor, photonic, or analog hardware. These systems are tested on event-camera vision, speech, time-series, robotics, and edge sensing, with benchmarks such as DVS Gesture, N-MNIST, SHD, and CIFAR variants. The central challenge is turning sparse activity and device-level efficiency into reliable end-to-end gains without sacrificing accuracy, scalability, or fair comparison with conventional hardware.

Latest papers

CardsList

194 papers15 papers in the last four weeks, down 25% on the four weeks before. 0.1% of all new papers.

  1. The role of neuromorphic principles in the future of biomedicine and healthcare

    Mar 29, 2026Grace M. Hwang, Jessica D. Falcone, Joseph D. Monaco +9Neuromorphic Computing

  2. An Energy-Efficient Spiking Neural Network Architecture for Predictive Insulin Delivery

    Mar 29, 2026Sahil ShrivastavaSpiking Neural NetworksEfficient Neural Network Inference

  3. Reconstructing Spiking Neural Networks Using a Single Neuron with Autapses

    Mar 25, 2026Wuque Cai, Hongze Sun, Quan Tang +6Spiking Neural NetworksNeuromorphic Computing

  4. Mixed-signal implementation of feedback-control optimizer for single-layer Spiking Neural Networks

    Mar 25, 2026Jonathan Haag, Christian Metzner, Dmitrii Zendrikov +4On-Device TrainingNeuromorphic Computing

  5. Machine vision with small numbers of detected photons per inference

    Mar 25, 2026Shi-Yuan Ma, Jérémie Laydevant, Mandar M. Sohoni +3Image ClassificationHardware-Software Co-Design

  6. Latency Coding for Efficient and Low-Latency Deep Spiking Neural Networks

    Mar 24, 2026Yi Lu, Jianhao Ding, Zhaofei YuEfficient Neural Network InferenceSpiking Neural Networks

  7. Event-Driven Neuromorphic Vision Enables Energy-Efficient Visual Place Recognition

    Mar 24, 2026Geoffroy Keime, Nicolas Cuperlier, Benoit R. CottereauVisual Place RecognitionNeuromorphic Computing

  8. Brain-inspired AI for Edge Intelligence: a systematic review

    Mar 19, 2026Yingchao Cheng, Meijia Wang, Zhifeng Hao +1Neuromorphic ComputingSpiking Neural Networks

  9. Linearized Bregman Iterations for Sparse Spiking Neural Networks

    Mar 17, 2026Daniel Windhager, Bernhard A. Moser, Michael LunglmayrSpiking Neural NetworksSparse Neural Networks

  10. Determinism in the Undetermined: Deterministic Output in Charge-Conserving Continuous-Time Neuromorphic Systems with Temporal Stochasticity

    Mar 16, 2026Jing Yan, Kang You, Zhezhi He +1Neuromorphic ComputingSpiking Neural Networks

  11. S2Act: Simple Spiking Actor

    Mar 16, 2026Ugur Akcal, Seung Hyun Kim, Mikihisa Yuasa +6Spiking Neural NetworksRobotic RL

  12. Benchmarking the Energy Cost of Assurance in Neuromorphic Edge Robotics

    Mar 14, 2026Sylvester KaczmarekAdversarial RobustnessNeuromorphic Computing

  13. SRAM-Based Compute-in-Memory Accelerator for Linear-decay Spiking Neural Networks

    Mar 13, 2026Hongyang Shang, Shuai Dong, Yahan Yang +3LIF NeuronsSpiking Neural Networks

  14. SNAP-V: A RISC-V SoC with Configurable Neuromorphic Acceleration for Small-Scale Spiking Neural Networks

    Mar 12, 2026Kanishka Gunawardana, Sanka Peeris, Kavishka Rambukwella +4Neuromorphic ComputingEfficient Neural Network Inference

  15. Stable Spike: Dual Consistency Optimization via Bitwise AND Operations for Spiking Neural Networks

    Mar 12, 2026Yongqi Ding, Kunshan Yang, Linze Li +3Spiking Neural NetworksNeuromorphic Computing

  16. Intrinsic Numerical Robustness and Fault Tolerance in a Neuromorphic Algorithm for Scientific Computing

    Mar 10, 2026Bradley H. Theilman, James B. AimoneNeuromorphic ComputingNeural Network Robustness

  17. DendroNN: Dendrocentric Neural Networks for Energy-Efficient Classification of Event-Based Data

    Mar 10, 2026Jann Krausse, Zhe Su, Kyrus Mama +4Efficient Neural Network InferenceSpiking Neural Networks

  18. Bullet Trains: Parallelizing Training of Temporally Precise Spiking Neural Networks

    Feb 27, 2026Todd Morrill, Christian Pehle, Anthony ZadorSpiking Neural NetworksNeuromorphic Computing

  19. Modelling and Simulation of Neuromorphic Datasets for Anomaly Detection in Computer Vision

    Feb 26, 2026Mike Middleton, Teymoor Ali, Hakan Kayan +6Synthetic Anomaly GenerationEvent-Based Vision

  20. Orthogonal Weight Modification Enhances Learning Scalability and Convergence Efficiency without Gradient Backpropagation

    Feb 25, 2026Guoqing Ma, Shan YuNeuromorphic ComputingSpiking Neural Networks

  21. ConformalHDC: Uncertainty-Aware Hyperdimensional Computing with Application to Neural Decoding

    Feb 24, 2026Ziyi Liang, Hamed Poursiami, Zhishun Yang +5Hyperdimensional ComputingNeuromorphic Computing

  22. Robust Spiking Neural Networks Against Adversarial Attacks

    Feb 24, 2026Shuai Wang, Malu Zhang, Yulin Jiang +7Adversarial RobustnessSpiking Neural Networks

  23. Memory-Augmented Spiking Networks: Synergistic Integration of Complementary Mechanisms for Neuromorphic Vision

    Feb 21, 2026Effiong Blessing, Chiung-Yi Tseng, Isaac Nkrumah +1Spiking Neural NetworksNeuromorphic Computing

  24. Flexi-NeurA: A Flexible Neuromorphic Accelerator with Adaptive Bit-Precision Exploration for Edge Devices

    Feb 20, 2026Mohammad Farahani, Mohammad Rasoul Roshanshah, Saeed SafariNeuromorphic ComputingFPGA Acceleration

  25. HiAER-Spike Software-Hardware Reconfigurable Platform for Event-Driven Neuromorphic Computing at Scale

    Feb 20, 2026Gwenevere Frank, Gopabandhu Hota, Keli Wang +12Neuromorphic ComputingEfficient Neural Network Inference