ae-foster / pyroLinks
Deep universal probabilistic programming with Python and PyTorch
☆12Updated 5 years ago
Alternatives and similar repositories for pyro
Users that are interested in pyro are comparing it to the libraries listed below
Sorting:
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
 - Variational Gaussian Process State-Space Models☆25Updated 9 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
 - PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
 - Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
 - Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
 - ☆15Updated 3 years ago
 - Heterogeneous Multi-output Gaussian Processes☆53Updated 5 years ago
 - Learning unknown ODE models with Gaussian processes☆27Updated 7 years ago
 - Max-value Entropy Search for Efficient Bayesian Optimization☆78Updated 3 years ago
 - Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch☆22Updated 5 years ago
 - Nonparametric Differential Equation Modeling☆56Updated last year
 - Python and MATLAB code for Stein Variational sampling methods☆26Updated 6 years ago
 - Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆44Updated 11 months ago
 - Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
 - Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆21Updated 3 years ago
 - Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆58Updated 4 years ago
 - Refining continuous-in-depth neural networks☆42Updated 3 years ago
 - 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
 - Release code for ICML2020 Knowing The What But Not The Where in Bayesian Optimization☆15Updated 2 years ago
 - [ICML 2021] Deep Learning for Functional Data Analysis with Adaptive Basis Layers☆30Updated 3 years ago
 - Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 9 years ago
 - Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
 - Bayesian Neural Network Surrogates for Bayesian Optimization☆63Updated last year
 - Code for "Causal autoregressive flows" - AISTATS, 2021☆45Updated 4 years ago
 - Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
 - Stochastic Gradient Langevin Dynamics for Bayesian learning☆35Updated 3 years ago
 - Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
 - code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆100Updated 6 years ago
 - Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago