patrick-kidger / NeuralCDE
Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
☆646Updated 2 years ago
Alternatives and similar repositories for NeuralCDE:
Users that are interested in NeuralCDE are comparing it to the libraries listed below
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆434Updated last year
- Code for "Latent ODEs for Irregularly-Sampled Time Series" paper☆550Updated 4 years ago
- Pytorch implementation of GRU-ODE-Bayes☆230Updated 2 years ago
- Pytorch implementation of Augmented Neural ODEs☆538Updated 2 years ago
- Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations☆744Updated last year
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆278Updated 3 years ago
- A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods☆1,463Updated 11 months ago
- Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series☆113Updated last year
- A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…☆1,418Updated 6 months ago
- code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".☆637Updated 4 years ago
- Differentiable computations of the signature and logsignature transforms, on both CPU and GPU. (ICLR 2021)☆268Updated last year
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆116Updated 3 years ago
- Differentiable SDE solvers with GPU support and efficient sensitivity analysis.☆1,624Updated 3 months ago
- Neural Graph Differential Equations (Neural GDEs)☆200Updated 3 years ago
- Linear and non-linear spectral forecasting algorithms☆137Updated 4 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- Normalizing flows in PyTorch☆896Updated 3 months ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆210Updated 5 months ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆437Updated 7 months ago
- TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155☆135Updated 2 years ago
- ODE2VAE: Deep generative second order ODEs with Bayesian neural networks☆127Updated 7 months ago
- This repository contains experiments with Neural Ordinary Differential Equations with simulated and real empirical data☆198Updated 5 years ago
- This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…☆305Updated 3 weeks ago
- [NeurIPS'19] Deep Equilibrium Models☆742Updated 2 years ago
- Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support☆218Updated 4 years ago
- Laplace approximations for Deep Learning.☆498Updated last month
- Masked Autoregressive Flow☆210Updated 8 months ago
- Experiments for Neural Flows paper☆94Updated 3 years ago
- Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"☆286Updated 4 years ago
- N-BEATS is a neural-network based model for univariate timeseries forecasting. N-BEATS is a ServiceNow Research project that was started …☆536Updated 2 years ago