cambridge-mlg / neural_diffusion_processesLinks
☆13Updated 2 years ago
Alternatives and similar repositories for neural_diffusion_processes
Users that are interested in neural_diffusion_processes are comparing it to the libraries listed below
Sorting:
- Neural Diffusion Processes☆82Updated last year
- [ICLR 2022] Path integral sampler☆52Updated 2 years ago
- Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral☆52Updated 3 years ago
- A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).☆20Updated last year
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 5 years ago
- Featurized Density Ratio Estimation☆20Updated 4 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆57Updated last year
- Official implementation of Transformer Neural Processes☆78Updated 3 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆18Updated 5 years ago
- NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models☆17Updated last year
- Methods and experiments for assumed density SDE approximations☆12Updated 4 years ago
- ☆37Updated 5 years ago
- ODE2VAE: Deep generative second order ODEs with Bayesian neural networks☆132Updated last year
- [ICML2022] Variational Wasserstein gradient flow☆24Updated 3 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆76Updated 3 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 4 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆89Updated 3 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆30Updated last year
- ☆18Updated 3 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 4 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆35Updated 3 years ago
- Implementation of Action Matching for the Schrödinger equation☆25Updated 2 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"☆20Updated 3 years ago
- ☆52Updated 2 years ago
- Code release for "Stochastic Optimal Control Matching"☆39Updated last year
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆21Updated 4 years ago