AVMCMC / AuxiliaryVariationalMCMCLinks
Code required to reproduce the experiments in Auxiliary Variational MCMC
☆17Updated 7 years ago
Alternatives and similar repositories for AuxiliaryVariationalMCMC
Users that are interested in AuxiliaryVariationalMCMC are comparing it to the libraries listed below
Sorting:
- ☆64Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆49Updated 5 years ago
- ☆54Updated last year
- Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch☆23Updated 5 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Code release for the ICLR paper☆21Updated 7 years ago
- Monotone operator equilibrium networks☆54Updated 5 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- ☆37Updated 5 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆57Updated last year
- ☆37Updated 3 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 4 years ago
- Sequential Neural Likelihood☆42Updated 6 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 3 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆21Updated 3 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 6 years ago
- Code for "Inference Suboptimality in Variational Autoencoders"☆14Updated 5 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 7 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 3 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 5 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- ☆52Updated 2 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- PyTorch implementation of Algorithm 1 of "On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models"☆38Updated last year
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago