andrew-cr / online_var_fil
Code for our paper: Online Variational Filtering and Parameter Learning
☆18Updated 2 years ago
Related projects: ⓘ
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆17Updated 2 years ago
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 5 years ago
- Sequential Neural Likelihood☆38Updated 5 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆63Updated 5 years ago
- ☆36Updated 4 years ago
- ☆49Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆27Updated 3 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 5 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆18Updated 5 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆37Updated last month
- ☆15Updated 2 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- ☆52Updated last month
- Kernel Identification Through Transformers☆12Updated last year
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆20Updated 3 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆18Updated 4 years ago
- Neural likelihood-free methods in PyTorch.☆38Updated 4 years ago
- Tree-structured recurrent switching linear dynamical systems☆34Updated 4 years ago
- Code for "Inference Suboptimality in Variational Autoencoders"☆14Updated 4 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆45Updated 3 years ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆25Updated last year
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆40Updated last year
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆58Updated 3 months ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Official code for UnICORNN (ICML 2021)☆27Updated 2 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆43Updated 6 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 2 years ago
- ☆35Updated last year