神经形态计算论文趋势 2023–2026

主要结论

• 神经形态计算论文从 2023 年的 18 篇增长到 2026 年的 35 篇，三年间扩大到约 1.9 倍。
• NeurIPS 是发神经形态计算论文最多的会议，2023–2026 年共 34 篇，占四个会议总量的 37%。
• 交叉方向里涨得最快的是应用 · neuroscience and cognitive science：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 12 篇。
• 在「量子与其他」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的光学计算是 1.2 倍，神经形态计算是 1.9 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• NeurIPS 2026Algebraic Machine Learning: learning as computing subsets of the subdirect decomposition from Abstract Algebra
• ICML 2026Equilibrium Propagation for Non-Conservative Systems
• ICLR 2026Beyond Linear Processing: Dendritic Bilinear Integration in Spiking Neural Networks
• CVPR 2026Reconstructing Spiking Neural Networks Using a Single Neuron with Autapses
• NeurIPS 2025Synergy Between the Strong and the Weak: Spiking Neural Networks are Inherently Self-Distillers
• ICML 2025Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model
• ICLR 2025Quantized Spike-driven Transformer
• CVPR 2025Spiking Transformer with Spatial-Temporal Attention
• NeurIPS 2024LibAMM: Empirical Insights into Approximate Computing for Accelerating Matrix Multiplication
• ICML 2024Robust Stable Spiking Neural Networks
• ICLR 2024Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks
• CVPR 2024DVMNet: Computing Relative Pose for Unseen Objects Beyond Hypotheses
• NeurIPS 2023Computing Approximate $\ell_p$ Sensitivities
• ICML 2023Dynamics-inspired Neuromorphic Visual Representation Learning
• ICLR 2023A Higher Precision Algorithm for Computing the $1$-Wasserstein Distance
• CVPR 2023Rate Gradient Approximation Attack Threats Deep Spiking Neural Networks
• NeurIPS 2026Computing All Optimal Partial $p$-Wasserstein Matchings on the Line
• ICML 2026Event2Vec: Processing neuromorphic events directly by representations in vector space
• ICLR 2026Breaking Gradient Temporal Collinearity for Robust Spiking Neural Networks
• CVPR 2026SDTrack A Baseline for Event-based Tracking via Spiking Neural Networks

全部神经形态计算论文

共 34 篇，第 1 / 1 页

1. NeurIPS 2026Algebraic Machine Learning: learning as computing subsets of the subdirect decomposition from Abstract Algebra
2. NeurIPS 2026Beyond Low-Pass Dynamics: Frequency-Selective Spiking Reservoirs with Resonant Neurons
3. NeurIPS 2026Computing All Optimal Partial $p$-Wasserstein Matchings on the Line
4. NeurIPS 2026Dimension Bounds for Contractive Reservoir Computing from Input Entropy
5. NeurIPS 2026Efficient Training of Deep Spiking Neural Networks with Input-Driven Derivative-Free Updates
6. NeurIPS 2026HPC-Bench: A Comprehensive Benchmark for High Performance Computing Codes
7. NeurIPS 2026Learning to play with spikes. Characterizing, predicting, and engineering unsupervised plasticity rules for spiking reservoir computing
8. NeurIPS 2026Precision As You Need: Stochastic Computing Is a Dense Adaptive Quantizer
9. NeurIPS 2026Spik-NeRF v2: Pushing the Limit of Spiking Neural Radiance Fields with $ \pm $I-LIF
10. NeurIPS 2026Spiking neural network initialization for scale-invariant maximization of entropy
11. NeurIPS 2025Bounds on the computational complexity of neurons due to dendritic morphology
12. NeurIPS 2025FRAM: Frobenius-Regularized Assignment Matching with Mixed-Precision Computing
13. NeurIPS 2025G-Net: A Provably Easy Construction of High-Accuracy Random Binary Neural Networks
14. NeurIPS 2025Multiplication-Free Parallelizable Spiking Neurons with Efficient Spatio-Temporal Dynamics
15. NeurIPS 2025S$^2$NN: Sub-bit Spiking Neural Networks
16. NeurIPS 2025Synergy Between the Strong and the Weak: Spiking Neural Networks are Inherently Self-Distillers
17. NeurIPS 2025The Parameterized Complexity of Computing the VC-Dimension
18. NeurIPS 2024Autonomous Driving with Spiking Neural Networks
19. NeurIPS 2024Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise
20. NeurIPS 2024LibAMM: Empirical Insights into Approximate Computing for Accelerating Matrix Multiplication
21. NeurIPS 2024QKFormer: Hierarchical Spiking Transformer using Q-K Attention
22. NeurIPS 2024Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks
23. NeurIPS 2024Slack-Free Spiking Neural Network Formulation for Hypergraph Minimum Vertex Cover
24. NeurIPS 2024Spike-based Neuromorphic Model for Sound Source Localization
25. NeurIPS 2024SpikedAttention: Training-Free and Fully Spike-Driven Transformer-to-SNN Conversion with Winner-Oriented Spike Shift for Softmax Operation
26. NeurIPS 2024Spiking Transformer with Experts Mixture
27. NeurIPS 2023Computing Approximate $\ell_p$ Sensitivities
28. NeurIPS 2023Computing Optimal Nash Equilibria in Multiplayer Games
29. NeurIPS 2023Energy-based learning algorithms for analog computing: a comparative study
30. NeurIPS 2023Evolving Connectivity for Recurrent Spiking Neural Networks
31. NeurIPS 2023Online learning of long-range dependencies
32. NeurIPS 2023Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies
33. NeurIPS 2023SEENN: Towards Temporal Spiking Early Exit Neural Networks
34. NeurIPS 2023Spike-driven Transformer

常见问题

2023–2026 年四大会议一共有多少篇神经形态计算论文？

共 92 篇，按年份分别是 2023 年 18 篇、2024 年 19 篇、2025 年 20 篇、2026 年 35 篇。

NeurIPS 2026 有多少篇神经形态计算论文？

NeurIPS 2026 有 10 篇神经形态计算论文，上一届是 7 篇。

ICLR 2026 有多少篇神经形态计算论文？

ICLR 2026 有 15 篇神经形态计算论文，上一届是 4 篇。

ICML 2026 有多少篇神经形态计算论文？

ICML 2026 有 8 篇神经形态计算论文，上一届是 6 篇。

CVPR 2026 有多少篇神经形态计算论文？

CVPR 2026 有 2 篇神经形态计算论文，上一届是 3 篇。

哪个会议的神经形态计算论文最多？

NeurIPS，2023–2026 年共 34 篇。