EliasNehme / NPPC
Official implementation of the NeurIPS 2023 paper: "Uncertainty Quantification via Neural Posterior Principal Components"
☆9Updated 9 months ago
Alternatives and similar repositories for NPPC:
Users that are interested in NPPC are comparing it to the libraries listed below
- Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with…☆55Updated 2 years ago
- Official implementation of "Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problems" paper.☆23Updated last year
- Learning Diffusion Priors from Observations by Expectation Maximization☆23Updated 2 weeks ago
- Differentiable and gpu enabled fast wavelet transforms in JAX.☆43Updated 8 months ago
- Official implementation of the paper "Normalization-Equivariant Neural Networks with Application to Image Denoising"☆12Updated 3 months ago
- Score-Based Priors for Bayesian Inverse Imaging (ICCV 2023, TMLR 2024)☆33Updated 3 months ago
- Conditional Invertible Neural Networks for Medical Imaging☆19Updated 2 years ago
- ☆22Updated 4 years ago
- Measuring the robustness of compressive sensing methods (including deep-learning-based ones) for image reconstruction.☆31Updated 3 years ago
- Implementation for the paper "PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization".☆21Updated last year
- ☆14Updated last year
- Official code for "Enabling Uncertainty Estimation in Iterative Neural Networks" (ICML 2024)☆16Updated 8 months ago
- Deep Probabilistic Imaging (DPI): Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging☆35Updated 2 years ago
- This is official Pytorch implementation of "Uncertainty quantification in medical image segmentation with Normalizing Flows", Raghavendra…☆30Updated 2 years ago
- [NeurIPS 2021] SNIPS: Solving Noisy Inverse Problems Stochastically☆50Updated 2 years ago
- Published in IEEE Trans. Comput. Imag.☆8Updated 5 months ago
- 🚀 A powerful library for efficient training of Neural Fields at scale.☆28Updated last year
- Code to reproduce results from "Invertible generative models for inverse problems: mitigating representation error and dataset bias"☆21Updated 4 years ago
- Code for the paper "Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification" (2020)☆43Updated 10 months ago
- Deep inverse problems in Python☆58Updated 2 years ago
- ☆32Updated 2 years ago
- Official repo for Trumpets: Injective Flows for Inference and Inverse Problems☆13Updated 3 years ago
- Code for the paper "Analyzing inverse problems with invertible neural networks." (2018)☆94Updated 5 years ago
- Adaptive, interpretable wavelets across domains (NeurIPS 2021)☆77Updated 3 years ago
- ☆13Updated 11 months ago
- ☆88Updated 3 years ago
- Official implementation of the paper "Solving Inverse Problems With Deep Neural Networks - Robustness Included?" by M. Genzel, J. Macdona…☆28Updated 2 years ago
- Code related to the paper "Deep Equilibrium Architectures for Inverse Problems in Imaging"☆37Updated 3 years ago
- ☆11Updated 3 years ago
- ☆16Updated last year