YuliaRubanova / latent_odeLinks
Code for "Latent ODEs for Irregularly-Sampled Time Series" paper
☆566Updated 4 years ago
Alternatives and similar repositories for latent_ode
Users that are interested in latent_ode are comparing it to the libraries listed below
Sorting:
- Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)☆682Updated 3 years ago
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆458Updated 2 months ago
- Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations☆787Updated last year
- Pytorch implementation of Augmented Neural ODEs☆551Updated 2 years ago
- Pytorch implementation of GRU-ODE-Bayes☆231Updated 3 years ago
- Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data☆220Updated 3 years ago
- Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series☆119Updated 2 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆227Updated last year
- TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155☆143Updated 2 years ago
- A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…☆1,494Updated last year
- code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".☆663Updated 5 years ago
- Neural Graph Differential Equations (Neural GDEs)☆210Updated 4 years ago
- This repository contains experiments with Neural Ordinary Differential Equations with simulated and real empirical data☆199Updated 6 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆63Updated 4 years ago
- ODE2VAE: Deep generative second order ODEs with Bayesian neural networks☆130Updated last year
- implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)☆99Updated 8 months ago
- PyTorch implementation of bayesian neural network [torchbnn]☆551Updated last year
- This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural P…☆1,005Updated 4 years ago
- A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods☆1,540Updated last year
- Pytorch implementation of Neural Processes for functions and images☆234Updated 3 years ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆464Updated last year
- ☆26Updated 5 years ago
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆238Updated 7 years ago
- Papers for Bayesian-NN☆326Updated 6 years ago
- A simple and extensible library to create Bayesian Neural Network layers on PyTorch.☆980Updated 2 years ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆197Updated 2 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆576Updated 3 years ago
- Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments☆405Updated last year
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆239Updated last year
- Differentiable SDE solvers with GPU support and efficient sensitivity analysis.☆1,685Updated 10 months ago