tfrerix / proxprop
Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps
☆42Updated 6 years ago
Alternatives and similar repositories for proxprop
Users that are interested in proxprop are comparing it to the libraries listed below
Sorting:
- ☆81Updated 7 years ago
- TensorFlow implementation of (Momentum) Stochastic Variance-Adapted Gradient.☆44Updated 7 years ago
- ScatWave is a Torch implementation of scattering using CUDA☆21Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago
- Implementation of "Learning with Random Learning Rates" in PyTorch.☆102Updated 5 years ago
- Second-order optimiser for deep networks☆76Updated 6 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆41Updated 6 years ago
- Implementation and demonstration of backdrop in pytorch. Code and demonstration of GP dataset generator.☆68Updated 6 years ago
- Odds and Ends and Things I've implemented.☆78Updated 6 years ago
- Code for paper "Convergent Learning: Do different neural networks learn the same representations?"☆86Updated 8 years ago
- TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials☆31Updated 7 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- boundary-seeking generative adversarial networks☆46Updated 7 years ago
- Implementation of the Deep Frank-Wolfe Algorithm -- Pytorch☆62Updated 4 years ago
- ☆29Updated 7 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Learning Deep Parsimonious Representations, Deep Learning, Clustering, NIPS 2016☆14Updated 5 years ago
- Forward-mode Automatic Differentiation for TensorFlow☆139Updated 7 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 7 years ago
- The Singular Values of Convolutional Layers☆72Updated 6 years ago
- Implementation of Coulomb GANs☆62Updated 3 years ago
- ☆26Updated 6 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- ☆32Updated 6 years ago
- Weight initialization schemes for PyTorch nn.Modules☆70Updated 8 years ago
- ☆42Updated 5 years ago
- Replication of the paper "Variational Dropout and the Local Reparameterization Trick" using Lasagne.☆33Updated 7 years ago
- ☆46Updated 7 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago