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
- Code for "Modeling Sparse Deviations for Compressed Sensing using Generative Models", ICML 2018☆24Updated 7 years ago
- Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)☆42Updated 5 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 6 years ago
- Deep convolutional gaussian processes.☆82Updated 6 years ago
- Tensorflow implementation of preconditioned stochastic gradient descent☆34Updated 2 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆184Updated 7 years ago
- Simple and extensible hypergradient for PyTorch☆18Updated 2 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Code release for the ICLR paper☆21Updated 7 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆26Updated 7 years ago
- Code to compute the Stein discrepancy between a sample distribution and its target☆17Updated 8 years ago
- Notebooks for IPAM Tutorial, March 15 2019☆24Updated 6 years ago
- Code for the Hamiltonian Variational Auto-Encoder from the proceedings of NeurIPS 2018☆16Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- Implementation of Hamiltonian Monte Carlo using Google's TensorFlow☆46Updated 10 years ago
- ☆25Updated 3 years ago
- Material for my Caltech tutorial on deep learning and tensor methods☆70Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Code for Fast Information-theoretic Bayesian Optimisation☆16Updated 7 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 6 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- ☆40Updated 6 years ago
- Source code for ICLR 2020 paper: "Learning to Guide Random Search"☆40Updated last year
- Nonlinear SVGD for Learning Diversified Mixture Models☆13Updated 7 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆58Updated 6 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 5 years ago