franrruiz / augment-reduceLinks
Code for Augment & Reduce, a scalable stochastic algorithm for large categorical distributions
☆10Updated 7 years ago
Alternatives and similar repositories for augment-reduce
Users that are interested in augment-reduce are comparing it to the libraries listed below
Sorting:
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆62Updated 5 years ago
- ☆20Updated 5 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 6 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- ☆24Updated 5 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆34Updated 3 years ago
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated 2 years ago
- Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…☆17Updated 5 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020☆36Updated 2 years ago
- ☆12Updated 5 years ago
- [AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution☆38Updated 4 years ago
- Keras implementation of Deep Wasserstein Embeddings☆48Updated 7 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 9 months ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated last year
- Large-batch Training, Neural Network Optimization☆9Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- ☆50Updated 4 years ago
- Deep Generative Models (Chainer)☆10Updated 7 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- ☆54Updated last year
- ☆43Updated 6 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 5 months ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆66Updated 5 years ago
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆41Updated last year
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago