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 6 years ago
- Implementation of paper "GibbsNet: Iterative Adversarial Inference for Deep Graphical Models" in PyTorch☆57Updated 7 years ago
- Code to accompany the paper "Learning Graphical State Transitions"☆171Updated 8 years ago
- Implementation of search-convolutional neural networks (SCNNs)☆51Updated 8 years ago
- Proceedings of ICML 2018☆39Updated 2 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
- Supplementary code to "Convolutional Neural Networks Generalization Utilizing the Data Graph Structure"☆51Updated 8 years ago
- Topics on theoretical, mathematical aspects of DL☆72Updated 8 years ago
- [ICLR 2019] Learning Representations of Sets through Optimized Permutations☆36Updated 6 years ago
- Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761☆37Updated 7 years ago
- RNNprop☆36Updated 8 years ago
- Code for "Generative Adversarial Training for Markov Chains" (ICLR 2017 Workshop)☆80Updated 7 years ago
- boundary-seeking generative adversarial networks☆46Updated 7 years ago
- Code for the paper "Learning sparse transformations through backpropagation"☆43Updated 5 years ago
- Code accompanying the paper Recurrent Relational Networks for Complex Relational Reasoning https://arxiv.org/abs/1711.08028☆202Updated 2 years ago
- Replication of the paper "Variational Dropout and the Local Reparameterization Trick" using Lasagne.☆33Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Survey of hyperparameter optimization use in NIPS2014☆12Updated 9 years ago
- Conditional variational autoencoder implementation in Torch☆105Updated 9 years ago
- Understanding Short-Horizon Bias in Stochastic Meta-Optimization☆37Updated 7 years ago
- BayesGrad: Explaining Predictions of Graph Convolutional Networks☆63Updated 3 years ago
- An iterative neural autoregressive distribution estimator (NADE-K)☆26Updated 10 years ago
- Deep variational inference in tensorflow☆56Updated 7 years ago
- Code to build VAE models that are jointly conditioned.☆36Updated 7 years ago
- PyMTL (Python library for Multi-task learning) is a Python module implementing a Multi-task learning framework built on top of scikit-lea…☆44Updated 11 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆101Updated 9 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Code accompanying the paper "Learning Permutations with Sinkhorn Policy Gradient"☆39Updated 6 years ago
- Code for the Santa algorithm for deep learning☆17Updated 7 years ago