hagabbar / cINNamon
Invertible neural network for gravitational wave parameter estimation
☆11Updated 2 years ago
Alternatives and similar repositories for cINNamon:
Users that are interested in cINNamon are comparing it to the libraries listed below
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- ☆20Updated 2 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- A pytorch version of hamiltonian monte carlo☆14Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Library for Deep Gaussian Processes based on GPflow☆19Updated 5 years ago
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆49Updated 4 years ago
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 5 years ago
- Gradient-informed particle MCMC methods☆11Updated last year
- Sequential Neural Likelihood☆40Updated 5 years ago
- Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…☆26Updated 10 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- A simple MCMC framework for training Gaussian processes adding functionality to GPy.☆21Updated 10 years ago
- Continual Gaussian Processes☆32Updated last year
- The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …☆14Updated 2 years ago
- Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation☆12Updated 3 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 4 years ago
- Super fast dynamic nested sampling with PolyChord (Python, C++ and Fortran likelihoods).☆22Updated 4 years ago
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- ☆30Updated 2 years ago
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 6 years ago
- ☆11Updated 4 years ago
- Continuous-time gradient flow for generative modeling and variational inference☆31Updated 6 years ago
- A Metropolis-Hastings MCMC sampler accelerated via diffusion models☆13Updated 9 months ago
- Stochastic variational heteroscedastic Gaussian process☆14Updated 6 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆30Updated 9 months ago
- A Python package for approximate Bayesian inference and optimization using Gaussian processes☆42Updated last year