rahulk90 / vae_sparseLinks
VAEs on Sparse Data
☆12Updated 7 years ago
Alternatives and similar repositories for vae_sparse
Users that are interested in vae_sparse are comparing it to the libraries listed below
Sorting:
- Replication of Semi-Supervised Learning with Deep Generative Models☆100Updated 9 years ago
- ☆74Updated 6 years ago
- Conditional variational autoencoder implementation in Torch☆107Updated 9 years ago
- Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761☆37Updated 7 years ago
- Variational Auto-encoder with Non-parametric Bayesian Prior☆43Updated 8 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 12 years ago
- Code for the icml paper "zero inflated exponential family embedding"☆29Updated 7 years ago
- Tensorflow implementation of Hyperspherical Variational Auto-Encoders☆232Updated 6 years ago
- Semi-Supervised Learning with Categorical VAE (experimented on MNIST)☆29Updated 8 years ago
- Variational Autoencoder with Recurrent Neural Network based on Google DeepMind's "DRAW: A Recurrent Neural Network For Image Generation"☆39Updated 8 years ago
- Implementation of paper "GibbsNet: Iterative Adversarial Inference for Deep Graphical Models" in PyTorch☆57Updated 7 years ago
- Deep generative models for semi-supervised learning.☆109Updated 8 years ago
- Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables☆13Updated 8 years ago
- Deriving Neural Architectures from Sequence and Graph Kernels☆59Updated 7 years ago
- Code for "Sequential Neural Models with Stochastic Layers"☆117Updated 8 years ago
- TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper☆51Updated 6 years ago
- Implementation of Sequential Variational Autoencoder☆90Updated 8 years ago
- ☆16Updated 8 years ago
- Determinantal point process☆19Updated 10 years ago
- TensorFlow implementation of the method from Variational Dropout Sparsifies Deep Neural Networks, Molchanov et al. (2017)☆16Updated 8 years ago
- TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials☆31Updated 7 years ago
- A variational recurrent neural network implementation in tensorflow☆104Updated 7 years ago
- This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…☆206Updated 7 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
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆38Updated 8 years ago
- Supplementary code to "Convolutional Neural Networks Generalization Utilizing the Data Graph Structure"☆50Updated 8 years ago
- Deep variational inference in tensorflow☆57Updated 7 years ago
- Asymmetric Transfer Learning with Deep Gaussian Processes☆18Updated 10 years ago