Mixed Noise and Posterior Estimation with Conditional DeepGEM
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Updated
Jul 5, 2024 - Python
Mixed Noise and Posterior Estimation with Conditional DeepGEM
Braid Normalizing Flows is a model of Anomaly Detection of images based of CS-Flow that uses a triplet of images to train
Normalising flows implemented using nflows
Awesome resources on normalizing flows.
Normalizing-flow enhanced sampling package for probabilistic inference in Jax
Normalizing flows for neuro-symbolic AI
[CVPR 2023] Code repository for HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution Estimation
Conditional normalizing flows (NFs), conditional GANs, and conditional variational autoencoders (CVAEs) with sklearn-like interface
Normalizing flows in PyTorch
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
[NeurIPS 2023] Training Energy-Based Normalizing Flow with Score-Matching Objectives
pocoMC: A Python implementation of Preconditioned Monte Carlo for accelerated Bayesian Computation
D<ee>p learning [dev library]
The official repository of BFSR: "Boosting Flow-based Generative Super-Resolution Models via Learned Prior" [CVPR 2024]
Official PyTorch code for UAI 2024 paper "ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-variable Context Encoding"
An extension of LightGBM to probabilistic modelling
nessai: Nested Sampling with Artificial Intelligence
PyTorch Lightning Implementation of Diffusion, GAN, VAE, Flow models
A flow-based generative ML model for calorimeter showers in particle detectors
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