edwardlib / observationsLinks
Tools for loading standard data sets in machine learning
☆204Updated 2 years ago
Alternatives and similar repositories for observations
Users that are interested in observations are comparing it to the libraries listed below
Sorting:
- Code for paper "L4: Practical loss-based stepsize adaptation for deep learning"☆124Updated 6 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
- Tensorflow implementation of Hyperspherical Variational Auto-Encoders☆232Updated 6 years ago
- Code for "Sequential Neural Models with Stochastic Layers"☆117Updated 8 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆359Updated 5 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 11 months ago
- Benchmark and build RL architectures that can do multitask and transfer learning.☆143Updated 2 years ago
- Some example scripts on pytorch☆198Updated 3 years ago
- Code accompanying the paper Recurrent Relational Networks for Complex Relational Reasoning https://arxiv.org/abs/1711.08028☆202Updated 2 years ago
- Experiments with differentiable stacks and queues in PyTorch☆142Updated 5 years ago
- Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al☆218Updated 6 years ago
- Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses☆186Updated last year
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆378Updated 8 years ago
- Implementation of VLAE☆215Updated 7 years ago
- Gumbel-Softmax Variational Autoencoder with Keras☆132Updated 7 years ago
- Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling☆91Updated 8 years ago
- Code for "Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer"☆244Updated 6 years ago
- Implementation of Sequential Variational Autoencoder☆88Updated 7 years ago
- Guided Evolutionary Strategies☆271Updated 2 years ago
- Understanding normalizing flows☆132Updated 5 years ago
- Tools for PyTorch☆222Updated 2 years ago
- Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832☆251Updated 6 years ago
- Implementation of Conditionally Shifted Neurons by Munkhdalai et al. (https://arxiv.org/pdf/1712.09926.pdf)☆28Updated 7 years ago
- ☆62Updated 8 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆140Updated 9 years ago
- Small Python library to automatically set CUDA_VISIBLE_DEVICES to the least loaded device on multi-GPU systems.☆107Updated 2 years ago
- Deep generative models for semi-supervised learning.☆108Updated 8 years ago
- Keras implementation of a Variational Auto Encoder with a Concrete Latent Distribution☆51Updated 7 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago