lokhande-vishnu / deepcgLinks
☆10Updated 7 years ago
Alternatives and similar repositories for deepcg
Users that are interested in deepcg are comparing it to the libraries listed below
Sorting:
- ☆135Updated 8 years ago
- Feasible target propagation code for the paper "Deep Learning as a Mixed Convex-Combinatorial Optimization Problem" by Friesen & Domingos…☆28Updated 7 years ago
- Gaussian Processes in Pytorch☆76Updated 5 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps☆42Updated 6 years ago
- Sparsifying Variational Dropout in Tensorflow☆22Updated 8 years ago
- Forward-mode Automatic Differentiation for TensorFlow☆139Updated 7 years ago
- Generative moment matching networks☆150Updated 9 years ago
- Code for paper "Full-Capacity Unitary Recurrent Neural Networks"☆54Updated 8 years ago
- meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)☆110Updated 3 years ago
- ☆62Updated 9 years ago
- Lua implementation of Entropy-SGD☆81Updated 7 years ago
- Python implementation of the infomration bottleneck method (tishby et al, 1999)☆36Updated 8 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 7 years ago
- Computing various norms/measures on over-parametrized neural networks☆50Updated 7 years ago
- hessian in pytorch☆187Updated 5 years ago
- Optimizing control variates for black-box gradient estimation☆163Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 5 years ago
- ☆12Updated 8 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆104Updated 9 years ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 7 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 6 years ago
- A generic Monte Carlo method based on the Gumbel-Max trick.☆32Updated 9 years ago
- code for steinGAN - Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning☆27Updated 6 years ago
- ☆46Updated 7 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆55Updated last year
- Code to reproduce some of the figures in the paper "On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima"☆145Updated 8 years ago
- Regularization, Neural Network Training Dynamics☆14Updated 6 years ago
- TensorFlow implementation of (Momentum) Stochastic Variance-Adapted Gradient.☆44Updated 7 years ago
- a light weight experiment reproducibility toolset☆40Updated 5 years ago