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The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a neural network.
Code associated with the work presented at ICLR and ICML 2022 workshops
A Python library for amortized Bayesian workflows using generative neural networks.
Deep Normalising Flows for stellar spectra. It's all about light.
Community-sourced list of papers and resources on neural simulation-based inference.
Diffusion Generative Modeling and Posterior Sampling in Simulation-Based Inference
Python Radiative Transfer in a Bayesian Framework
[Official] code for paper "Conditional diffusions for neural posterior estimation".
Supporting code for our paper "Protein Sequence Modelling with Bayesian Flow Networks"
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
Denoising Diffusion Probabilistic Models
TorchCFM: a Conditional Flow Matching library
A mini-library for training consistency models.
Official repo for consistency models.
Diffusion model papers, survey, and taxonomy
Official repo for "Solving Inverse Problems in Medical Imaging with Score-Based Generative Models"
Machine learning Algorithm for Radiative transfer of Generated Exoplanets
PyTorch implementation of Variational Diffusion Models.
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Code for reproducing results in the sliced score matching paper (UAI 2019)