Alternatives and similar repositories for torch-neural-ssm

Users that are interested in torch-neural-ssm are comparing it to the libraries listed below

• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆99Updated 3 years ago
• paulbrodersen / entropy_estimators
  Estimators for the entropy and other information theoretic quantities of continuous distributions
  ☆146Updated last year
• helange23 / from_fourier_to_koopman
  Linear and non-linear spectral forecasting algorithms
  ☆138Updated 4 years ago
• sdascoli / odeformer
  ☆69Updated last year
• gatsby-sahani / gp-sde
  ☆15Updated 2 years ago
• aangelopoulos / conformal-time-series
  Conformal prediction for time-series applications.
  ☆130Updated 2 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆50Updated 2 years ago
• blindedjoy / RcTorch
  a PyTorch based Reservoir Computing package with Automatic Hyper-Parameter Tuning
  ☆46Updated 2 years ago
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆63Updated 2 weeks ago
• crispitagorico / sigkernel
  Differentiable computations for the signature-PDE-kernel on CPU and GPU.
  ☆56Updated last month
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆75Updated 2 years ago
• josephbakarji / deep-delay-autoencoder
  Discovers high dimensional models from 1D data using deep delay autoencoders
  ☆37Updated 2 years ago
• TyXe-BDL / TyXe
  ☆155Updated 3 years ago
• Rose-STL-Lab / CopulaCPTS
  Code for Copula conformal prediction paper (ICLR 2024)
  ☆30Updated last year
• forgi86 / pytorch-ident
  System identification in PyTorch
  ☆27Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆75Updated 3 years ago
• clegaard / deep_learning_for_dynamical_systems
  ☆89Updated 2 years ago
• lindermanlab / ssm-jax
  Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend
  ☆61Updated last year
• pvlachas / RNN-RC-Chaos
  RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical sy…
  ☆96Updated 2 years ago
• cvxgrp / signal-decomposition
  A simple and general framework for signal decomposition
  ☆73Updated 10 months ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆240Updated last year
• williamgilpin / fnn
  Embed strange attractors using a regularizer for autoencoders
  ☆135Updated 4 years ago
• simonmoesorensen / neural-ode-project
  Deeplearning project at The Technological University of Denmark (DTU) about Neural ODEs for finding dynamics in ordinary differential equ…
  ☆17Updated 3 years ago
• TUM-ITR / koopcore
  Koopman Kernels for Learning Dynamical Systems from Trajectory Data
  ☆31Updated 2 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 3 years ago
• yongkyung-oh / Stable-Neural-SDEs
  [ICLR 2024] Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
  ☆61Updated 3 months ago
• hamrel-cxu / EnbPI
  Official code for: Conformal prediction interval for dynamic time-series (conference, ICML 21 Long Presentation) AND Conformal prediction…
  ☆129Updated 2 years ago
• kamilest / conformal-rnn
  Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
  ☆77Updated last year
• jamesross2 / Bayesian-HMM
  A non-parametric Bayesian approach to Hidden Markov Models
  ☆86Updated 2 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year