renmengye / tensorflow-forward-ad
Forward-mode Automatic Differentiation for TensorFlow
☆139Updated 7 years ago
Alternatives and similar repositories for tensorflow-forward-ad:
Users that are interested in tensorflow-forward-ad are comparing it to the libraries listed below
- Evaluation code with models for the paper "On the Quantitative Analysis of Decoder-Based Generative Models"☆130Updated 7 years ago
- Weight initialization schemes for PyTorch nn.Modules☆70Updated 8 years ago
- Code for paper "L4: Practical loss-based stepsize adaptation for deep learning"☆125Updated 6 years ago
- Malmo Collaborative AI Challenge - Team Pig Catcher☆65Updated 7 years ago
- Code for Attentive Recurrent Comparators☆57Updated 8 years ago
- Implementation of Coulomb GANs☆62Updated 3 years ago
- DeepArchitect: Automatically Designing and Training Deep Architectures☆145Updated 5 years ago
- Weight initialisation schemes for Torch7 neural network modules☆100Updated 7 years ago
- Cluttered MNIST Dataset☆51Updated 10 years ago
- Efficient layer normalization GPU kernel for Tensorflow☆111Updated 8 years ago
- Topics on theoretical, mathematical aspects of DL☆72Updated 8 years ago
- Tensorflow Implementation on "The Cramer Distance as a Solution to Biased Wasserstein Gradients" (https://arxiv.org/pdf/1705.10743.pdf)☆125Updated 7 years ago
- A Tensorfflow implementation of Attend, Infer, Repeat☆81Updated 6 years ago
- Variational and semi-supervised neural network toppings for Lasagne☆208Updated 8 years ago
- Code to train Importance Weighted Autoencoders on MNIST and OMNIGLOT☆206Updated 9 years ago
- ☆133Updated 7 years ago
- Neural network training using iterated projections.☆89Updated 8 years ago
- PixelVAE with or without regularization☆66Updated 7 years ago
- Probabilistic Programming and Statistical Inference in PyTorch☆110Updated 7 years ago
- Decoupled Neural Interfaces using Synthetic Gradients for PyTorch☆237Updated 6 years ago
- ☆38Updated 8 years ago
- repository for the Variational Autoencoder (VAE) blogpost series from Fast Forward Labs☆103Updated 8 years ago
- Second-order optimiser for deep networks☆76Updated 6 years ago
- auto-tuning momentum SGD optimizer☆287Updated 6 years ago
- ☆63Updated 8 years ago
- Implementation of "Learning with Random Learning Rates" in PyTorch.☆102Updated 5 years ago
- Capsule network with variations. Originally proposed by Tieleman & Hinton : http://www.cs.toronto.edu/~tijmen/tijmen_thesis.pdf☆170Updated 7 years ago
- Tensorflow implementation of SGD with Coupled Adaptive Batch Size (CABS)☆43Updated 8 years ago
- Learning Deep Parsimonious Representations, Deep Learning, Clustering, NIPS 2016☆14Updated 5 years ago
- ☆79Updated 7 years ago