JTT94 / filterflow
Extensible Tensorflow library for differentiable particle filtering. ICML 2021.
☆41Updated 2 years ago
Alternatives and similar repositories for filterflow:
Users that are interested in filterflow are comparing it to the libraries listed below
- Code for efficiently sampling functions from GP(flow) posteriors☆71Updated 4 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- ☆50Updated 2 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.☆31Updated last year
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated last year
- Gaussian Processes for Sequential Data☆18Updated 4 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆102Updated last year
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 8 months ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"☆59Updated 4 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆98Updated last year
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- ☆29Updated 2 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- A generic interface for linear algebra backends☆73Updated last month
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Normalizing Flows using JAX☆83Updated last year
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Bayesian inference with Python and Jax.☆32Updated 2 years ago
- Zheng Zhao's doctoral dissertation from Aalto University☆34Updated 2 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆124Updated 5 months ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 2 years ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Companion code in JAX for the paper Parallel Iterated Extended and Sigma-Point Kalman Smoothers.☆26Updated 7 months ago