Sohl-Dickstein / Hamiltonian-Annealed-Importance-SamplingLinks
Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimation for models with continuous state spaces
☆26Updated 11 years ago
Alternatives and similar repositories for Hamiltonian-Annealed-Importance-Sampling
Users that are interested in Hamiltonian-Annealed-Importance-Sampling are comparing it to the libraries listed below
Sorting:
- Code to produce demos of Metroplis-Hastings and Hamiltonian Monte Carlo samplers.☆36Updated 11 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Machine Learning Function Approximation: This code implements the fully-connected Deep Neural Network (DNN) architectures considered in t…☆18Updated 5 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- orbital MCMC☆10Updated 4 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- A pytorch version of hamiltonian monte carlo☆15Updated 6 years ago
- ☆50Updated last year
- Python and MATLAB code for Stein Variational sampling methods☆26Updated 6 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆19Updated 4 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆21Updated 3 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆26Updated 7 years ago
- Monotone operator equilibrium networks☆53Updated 5 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 9 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 6 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Matlab code implementing Minimum Probability Flow Learning.☆69Updated 11 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 3 years ago
- Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)☆18Updated 7 years ago
- ☆40Updated 6 years ago
- ☆22Updated 5 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago
- Code for Non-convex Learning via Replica Exchange Stochastic Gradient MCMC, ICML 2020.☆26Updated 4 years ago
- Prototypes of differentiable differential equation solvers in JAX.☆27Updated 5 years ago
- We got a stew going!☆27Updated 2 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- ☆15Updated 3 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 6 years ago
- ☆25Updated 7 years ago