taolei87 / icml17_knnLinks
Deriving Neural Architectures from Sequence and Graph Kernels
☆59Updated 7 years ago
Alternatives and similar repositories for icml17_knn
Users that are interested in icml17_knn are comparing it to the libraries listed below
Sorting:
- pytorch implementation of grammar variational autoencoder☆63Updated 7 years ago
- Implementation of search-convolutional neural networks (SCNNs)☆51Updated 8 years ago
- Code to accompany the paper "Learning Graphical State Transitions"☆171Updated 8 years ago
- Implementation of paper "GibbsNet: Iterative Adversarial Inference for Deep Graphical Models" in PyTorch☆57Updated 7 years ago
- BayesGrad: Explaining Predictions of Graph Convolutional Networks☆63Updated 3 years ago
- Supplementary code to "Convolutional Neural Networks Generalization Utilizing the Data Graph Structure"☆49Updated 8 years ago
- boundary-seeking generative adversarial networks☆46Updated 7 years ago
- Code to build VAE models that are jointly conditioned.☆36Updated 7 years ago
- A Lasagne and Theano implementation of the paper Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, and Ian Goodfellow.☆41Updated 9 years ago
- ☆76Updated 8 years ago
- Topics on theoretical, mathematical aspects of DL☆72Updated 8 years ago
- Deep variational inference in tensorflow☆57Updated 7 years ago
- Code for paper "Full-Capacity Unitary Recurrent Neural Networks"☆54Updated 8 years ago
- Code for "Generative Adversarial Training for Markov Chains" (ICLR 2017 Workshop)☆81Updated 8 years ago
- RNNprop☆36Updated 8 years ago
- Evaluation code with models for the paper "On the Quantitative Analysis of Decoder-Based Generative Models"☆130Updated 8 years ago
- This contains my M.Tech project work on using Deep Leanring for learning graph representations. Data will be provided on request☆33Updated 8 years ago
- An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU…☆72Updated 7 years ago
- [ICLR 2019] Learning Representations of Sets through Optimized Permutations☆36Updated 6 years ago
- code for fast dropout☆46Updated 9 years ago
- Understanding Short-Horizon Bias in Stochastic Meta-Optimization☆37Updated 7 years ago
- Conditional variational autoencoder implementation in Torch☆107Updated 9 years ago
- ☆85Updated 10 years ago
- Code accompanying the paper "Learning Permutations with Sinkhorn Policy Gradient"☆39Updated 7 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆103Updated 9 years ago
- Code for the paper "Learning sparse transformations through backpropagation"☆43Updated 5 years ago
- ☆62Updated 8 years ago
- Material for the EPFL master course "A Network Tour of Data Science", edition 2016.☆99Updated 5 years ago
- Implementation of the reweighted wake-sleep machine learning algorithm☆42Updated 9 years ago
- Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761☆37Updated 7 years ago