guxd / deepHMM
A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]
☆56Updated 8 months ago
Alternatives and similar repositories for deepHMM:
Users that are interested in deepHMM are comparing it to the libraries listed below
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆46Updated last year
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 2 years ago
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.☆37Updated last year
- ☆51Updated 8 months ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"☆38Updated 2 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Gaussian processes with PyTorch☆30Updated 3 years ago
- implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)☆92Updated last year
- PyTorch implementation of Stein Variational Gradient Descent☆43Updated last year
- PyTorch re-implementation of [Structured Inference Networks for Nonlinear State Space Models, AAAI 17]☆24Updated 4 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆116Updated 3 years ago
- ☆47Updated 2 years ago
- ☆38Updated 4 years ago
- ☆90Updated 2 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Kalman Variational Auto-Encoder☆135Updated 6 years ago
- Contrastive Learning for Time Series☆38Updated last year
- A Recurrent Latent Variable Model for Sequential Data☆24Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series☆113Updated last year
- Dirichlet-Variational Auto-Encoder by PyTorch☆22Updated last year
- code for "Neural Jump Ordinary Differential Equations"☆29Updated 2 years ago
- Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)☆58Updated last year
- Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Su…☆77Updated last year
- TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155☆135Updated 2 years ago
- Pytorch implementation of Recurrent Neural Processes https://arxiv.org/pdf/1906.05915.pdf☆21Updated 5 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 4 years ago