Popular GitHub Repositories for Density Peaks

Awesome resources on normalizing flows.

Normalizing flows in PyTorch

An extension of XGBoost to probabilistic modelling

PyTorch implementations of algorithms for density estimation

DanceNet -??Dance generator using Autoencoder, LSTM and Mixture Density Network. (Keras)

Normalizing flows in PyTorch

A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)

Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].

An extension of LightGBM to probabilistic modelling

Density-aware Single Image De-raining using a Multi-stream Dense Network (CVPR 2018)

Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.

[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"

Pytorch implementation of Block Neural Autoregressive Flow

An MDN Layer for Keras using TensorFlow's distributions module

A collection of Nerual Network Models for chemistry

Likelihood-free AMortized Posterior Estimation with PyTorch

A JAX implementation of DEformer for arbitrary conditioning.

Official code of the paper "Expanding Low-Density Latent Regions for Open-Set Object Detection" (CVPR 2022)

Neural Relation Understanding: neural cardinality estimators for tabular data

GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine learning techniques.