QUANTA-github / information-geometryLinks
Information Geometry
☆12Updated 4 years ago
Alternatives and similar repositories for information-geometry
Users that are interested in information-geometry are comparing it to the libraries listed below
Sorting:
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Deep convolutional gaussian processes.☆80Updated 5 years ago
- Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)☆42Updated 5 years ago
- Notebooks for IPAM Tutorial, March 15 2019☆24Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Code for "Modeling Sparse Deviations for Compressed Sensing using Generative Models", ICML 2018☆24Updated 7 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆183Updated 7 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆25Updated 7 years ago
- Code for Fast Information-theoretic Bayesian Optimisation☆16Updated 7 years ago
- Material for my Caltech tutorial on deep learning and tensor methods☆70Updated 6 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆56Updated 6 years ago
- Code for the Hamiltonian Variational Auto-Encoder from the proceedings of NeurIPS 2018☆15Updated 5 years ago
- TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials☆31Updated 7 years ago
- The code for Meta Learning for SGMCMC☆25Updated 6 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- ☆25Updated 3 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- Implementation of the Sliced Wasserstein Autoencoders☆90Updated 7 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- gpbo☆25Updated 4 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Nonlinear SVGD for Learning Diversified Mixture Models☆13Updated 6 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 6 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Several implementations of the kernel-based activation functions☆62Updated 6 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- ☆82Updated 7 years ago