ernoult / targetProp
Testing Difference Target Propagation (DTP) on MNIST.
☆12Updated 4 years ago
Alternatives and similar repositories for targetProp:
Users that are interested in targetProp are comparing it to the libraries listed below
- Python implementation of the methods in Meulemans et al. 2020 - A Theoretical Framework For Target Propagation☆32Updated 6 months ago
- Automatic Hebbian learning in multi-layer convolutional networks with PyTorch, by expressing Hebbian plasticity rules as gradients☆38Updated last year
- Public code for Illing, Ventura, Bellec & Gerstner 2021: Local plasticity rules can learn deep representations using self-supervised cont…☆24Updated last year
- "Towards Scaling Difference Target Propagation by Learning Backprop Targets" (ICML 2022)☆12Updated 2 years ago
- ☆28Updated 6 years ago
- Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input (NeurIPS 2019)☆13Updated last year
- Code for "Deep predictive coding network for object recognition"☆25Updated 5 years ago
- ☆14Updated 3 years ago
- Official code for Coupled Oscillatory RNN (ICLR 2021, Oral)☆44Updated 3 years ago
- Implementation of feedback alignment learning in PyTorch☆31Updated last year
- Study on the applicability of Direct Feedback Alignment to neural view synthesis, recommender systems, geometric learning, and natural la…☆88Updated 2 years ago
- Project for the Large Scale Optimization course at Skoltech☆22Updated 6 years ago
- A lightweight and flexible framework for Hebbian learning in PyTorch.☆87Updated last year
- Padé Activation Units: End-to-end Learning of Activation Functions in Deep Neural Network☆64Updated 4 years ago
- Code for "Deep predictive coding network with local recurrent processing for object recognition"☆28Updated 8 months ago
- [ECMLPKDD 2020] "Topological Insights into Sparse Neural Networks"☆13Updated 3 years ago
- A PyTorch implementation of EventProp [https://arxiv.org/abs/2009.08378], a method to train Spiking Neural Networks☆49Updated 4 years ago
- BioTorch is a PyTorch framework specializing in biologically plausible learning algorithms☆50Updated last year
- PyTorch implementation of linear and convolutional layers with fixed, random feedback weights.☆14Updated 4 years ago
- PyTorch Lightning utilities that make it easier to train and evaluate deep models for the Neural Latents Benchmark.☆8Updated 2 years ago
- Functional Regularisation for Continual Learning with Gaussian Processes☆14Updated 4 years ago
- Deep Learning without Weight Transport☆35Updated 5 years ago
- Fully documented Pytorch implementation of the Equilibrium Propagation algorithm.☆34Updated 5 years ago
- Implementation of the Legendre Memory Unit in PyTorch☆22Updated 5 years ago
- ☆28Updated last year
- Neurons learn by predicting future activity☆28Updated 3 years ago
- Source code for paper Choromanska et al. -- Beyond Backprop: Online Alternating Minimization with Auxiliary Variables -- http://proceedin…☆24Updated 5 years ago
- The code for performing MTL on object recognition with neural data☆15Updated 3 years ago
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 5 years ago
- Delta Orthogonal Initialization for PyTorch☆18Updated 6 years ago