yjlolo / pytorch-deep-markov-model
PyTorch re-implementation of [Structured Inference Networks for Nonlinear State Space Models, AAAI 17]
☆24Updated 4 years ago
Alternatives and similar repositories for pytorch-deep-markov-model:
Users that are interested in pytorch-deep-markov-model are comparing it to the libraries listed below
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated last year
- Differentiable computations for the signature-PDE-kernel on CPU and GPU.☆53Updated 10 months ago
- Code for Hidden Markov Nonlinear ICA☆24Updated 3 years ago
- A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]☆56Updated 8 months ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Methods and experiments for assumed density SDE approximations☆11Updated 3 years ago
- Taylor moment expansion in Python (JaX and SymPy) and Matlab☆11Updated 4 months ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 2 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- code for "Neural Jump Ordinary Differential Equations"☆29Updated 2 years ago
- Implementation of the ICML 2024 paper "Discovering Mixtures of Structural Causal Models from Time Series Data"☆21Updated 5 months ago
- ☆47Updated 2 years ago
- An encoder-decoder framework for learning from incomplete data☆46Updated last year
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- TIme series DiscoverY BENCHmark (tidybench)☆37Updated last year
- Signax: Signature computation in JAX☆28Updated 2 months ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆58Updated 4 years ago
- implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)☆92Updated last week
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 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
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆86Updated 3 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- ☆26Updated last year
- Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"☆38Updated 2 years ago
- ☆63Updated last year
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 9 months ago