christina-winkler / cnfs-super-resolutionLinks
Master thesis for the MSc. Artificial Intelligence at the University of Amsterdam, 2019. Topic: Super-resolution with Conditional Normalizing Flows.
☆20Updated last year
Alternatives and similar repositories for cnfs-super-resolution
Users that are interested in cnfs-super-resolution are comparing it to the libraries listed below
Sorting:
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆226Updated last year
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 5 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Implementation of the Convolutional Conditional Neural Process☆127Updated 4 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Pytorch implementation of Neural Processes for functions and images☆233Updated 3 years ago
- Toy Examples of Conditional Density Estimation with Bayesian Normalizing flows☆21Updated 7 years ago
- Ladder Variational Autoencoders (LVAE) in PyTorch☆92Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Official implementation of Transformer Neural Processes☆78Updated 3 years ago
- Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch☆22Updated 5 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆18Updated 5 years ago
- Implementation of normalizing flows in TensorFlow 2 including a small tutorial.☆147Updated last month
- A Pytorch Implementation of Attentive Neural Process☆75Updated 6 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)☆99Updated 7 months ago
- Mixture density network implemented in PyTorch.☆152Updated 2 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆63Updated 4 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆59Updated last year
- Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982☆22Updated 4 years ago
- ☆37Updated 5 years ago
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 6 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆120Updated 4 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆46Updated 2 years ago
- Vector Quantile Regression☆19Updated 7 months ago
- We got a stew going!☆27Updated 2 years ago