geosada / LVAELinks
LVAE: Ladder Variational Auto-Encoders (NIPS 2016) with TensorFlow.
☆16Updated 7 years ago
Alternatives and similar repositories for LVAE
Users that are interested in LVAE are comparing it to the libraries listed below
Sorting:
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago
- ☆91Updated 6 years ago
- Implementation of different Normalizing Flows, NF, Planar Flows, IAF, etc.☆30Updated 7 years ago
- Pytorch Adversarial Auto Encoder (AAE)☆87Updated 6 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Deep Generative Models (Chainer)☆10Updated 7 years ago
- Sliced Wasserstein Generator☆23Updated 6 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆54Updated 6 years ago
- Uncertainty interpretations of the neural network☆32Updated 7 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adri à Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models☆154Updated 6 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆68Updated 5 years ago
- Keras implementation of Deep Wasserstein Embeddings☆48Updated 7 years ago
- PyTorch implementation of Neural Processes☆89Updated 6 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 7 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- In this paper, we show that the performance of a learnt generative model is closely related to the model's ability to accurately represen…☆41Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Implementation of Information Dropout☆39Updated 8 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- This repository tries to provide unsupervised deep learning models with Pytorch☆90Updated 7 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆102Updated 6 years ago
- ☆24Updated 5 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 11 months ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- ☆53Updated 7 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago