Research map / Architectures and efficiency / Spiking networks
Long short-term memory and Learning-to-learn in networks of spiking neurons
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add adapting neurons to the spiking network (ablation) | LSNN · TIMIT | classification error: 37% -> 33.2% | Helped |
| Add adapting neurons to the spiking network | LSNN · Sequential MNIST | classification accuracy | Helped |
| Use DEEP R rewiring to produce a sparse architecture | LSNN · Sequential MNIST | classification accuracy | Helped |
| Use sparse connectivity with rewiring instead of full connectivity (ablation) | LSNN learning target functions from a teacher · Target-function learning | mean squared error | No clear effect |
| Train the LSNN in an outer loop across related target tasks, then keep its weights fixed for online learning | LSNN · Learning nonlinear target functions from a teacher | mean squared error | Helped |
| Use a learned recurrent spiking learning algorithm rather than direct BP on an ANN | LSNN · Learning nonlinear target functions from a teacher | number of examples needed for learning | Helped |
| Train the LSNN with meta-RL across navigation tasks | LSNN agent · Arena navigation | number of goals reached | Helped |
Closest papers by meaning
- Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN (ICLR 2024 · similarity 0.89)
- GRSN: Gated Recurrent Spiking Neurons for POMDPs and MARL (AAAI 2025 · similarity 0.87)
- Learning the Plasticity: Plasticity-Driven Learning Framework in Spiking Neural Networks (NeurIPS 2025 · similarity 0.87)
- A Scalable, Causal, and Energy Efficient Framework for Neural Decoding with Spiking Neural Networks (NeurIPS 2025 · similarity 0.87)
- Temporal Flexibility in Spiking Neural Networks: Towards Generalization Across Time Steps and Deployment Friendliness (ICLR 2025 · similarity 0.87)
- Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings (ICLR 2024 · similarity 0.87)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.