guillaumeBellec / deep_rewiringLinks
Quick tutorial to Deep Rewiring
☆13Updated 6 years ago
Alternatives and similar repositories for deep_rewiring
Users that are interested in deep_rewiring are comparing it to the libraries listed below
Sorting:
- To identify features by aggregate-label learning in spiking neurons☆14Updated 7 years ago
- Implementation of NeurIPS 2019 paper "Normalization Helps Training of Quantized LSTM"☆31Updated 10 months ago
- Experiments with spiking neural networks (SNNs) in PyTorch. See https://github.com/BINDS-LAB-UMASS/bindsnet for the successor to this pro…☆90Updated 7 years ago
- PyTorch Implementation of “Unsupervised learning by competing hidden units” MNIST classifier☆12Updated 6 years ago
- Implementation of ICLR 2017 paper "Loss-aware Binarization of Deep Networks"☆18Updated 6 years ago
- Sparse Recurrent Neural Networks -- Pruning Connections and Hidden Sizes (TensorFlow)☆74Updated 4 years ago
- Code for the paper "Training Binary Neural Networks with Bayesian Learning Rule☆39Updated 3 years ago
- Training wide residual networks for deployment using a single bit for each weight - Official Code Repository for ICLR 2018 Published Pape…☆36Updated 5 years ago
- ☆53Updated 6 years ago
- This is the PyNN code used in the paper titled "Multilayer Spiking Neural Network for audio samples classification using SpiNNaker", whic…☆32Updated 3 years ago
- Learning-Recurrent-Binary-Ternary-Weights☆12Updated 6 years ago
- Proximal Mean-field for Neural Network Quantization☆22Updated 5 years ago
- custom cuda kernel for {2, 3}d relative attention with pytorch wrapper☆43Updated 5 years ago
- ☆114Updated last year
- ☆71Updated 9 years ago
- Profiling power consumption of a neuromorphic keyword spotter.☆22Updated 5 years ago
- Implementation of BinaryConnect on Pytorch☆39Updated 4 years ago
- Code from our paper: SuperSpike: Supervised learning in multi-layer spiking neural networks.☆56Updated 6 years ago
- ☆19Updated 7 years ago
- Stochastic Adaptive Neural Architecture Search☆65Updated 6 years ago
- Implementation of ICLR 2018 paper "Loss-aware Weight Quantization of Deep Networks"☆26Updated 5 years ago
- Delta Orthogonal Initialization for PyTorch☆18Updated 6 years ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 6 years ago
- A machine learning library for PyTorch☆92Updated 2 years ago
- Lookahead: A Far-sighted Alternative of Magnitude-based Pruning (ICLR 2020)☆33Updated 4 years ago
- Deep Learning without Weight Transport☆35Updated 5 years ago
- ☆103Updated 7 years ago
- ☆32Updated 6 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago
- A tutorial on 'Soft weight-sharing for Neural Network compression' published at ICLR2017☆145Updated 8 years ago