cagatayyildiz / ODE2VAE
ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
☆126Updated 6 months ago
Alternatives and similar repositories for ODE2VAE:
Users that are interested in ODE2VAE are comparing it to the libraries listed below
- Official code for the ICLR 2021 paper Neural ODE Processes☆71Updated 2 years ago
- Experiments for Neural Flows paper☆94Updated 3 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆86Updated 2 years ago
- This repository contains code released by DiffEqML Research☆89Updated 3 years ago
- Regularized Neural ODEs (RNODE)☆82Updated 3 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆57Updated 5 months ago
- Implementation of the Convolutional Conditional Neural Process☆121Updated 3 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆58Updated 4 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆104Updated 4 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆116Updated last year
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆52Updated 3 years ago
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆278Updated 3 years ago
- Pytorch implementation of Neural Processes for functions and images☆228Updated 3 years ago
- Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series☆113Updated last year
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 2 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆54Updated 4 years ago
- ☆45Updated last year
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Manifold-learning flows (ℳ-flows)☆229Updated 4 years ago
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆231Updated 6 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆51Updated 7 months ago
- Riemannian Convex Potential Maps☆67Updated last year
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Masked Autoregressive Flow☆210Updated 7 months ago
- ☆179Updated 5 years ago
- Experiments for the Neural Autoregressive Flows paper☆123Updated 3 years ago
- ☆45Updated 4 years ago