Deep nonparametric estimation of discrete conditional distributions via smoothed dyadic partitioning
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Updated
Apr 19, 2017 - Python
Deep nonparametric estimation of discrete conditional distributions via smoothed dyadic partitioning
ML algorithm for real-time classification
Python package for nonparametric methods for density estimation and comparison https://doi.org/10.1080/03610918.2018.1484480
Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
Fast local density clustering for low-dimensional data
Code for reproducing Flow ++ experiments
Density Estimation and Anomaly Detection with Normalizing Flows
Libary for SGPD (Sigmoidal Gaussian Process Density) inference
A collection of commonly used datasets as benchmarks for density estimation in MaLe
Code for reproducing results in the sliced score matching paper (UAI 2019)
Implementation of non-linear independent components estimation (NICE) in pytorch
Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
Code for variable skipping ICML 2020 paper
PyTorch Implementation of the paper 'Density Estimation Using Real NVP' (ICLR 2017)
Library for Normalizing Flow in TensorFlow 2.0.
PyTorch implementation of MADE
My framework to perform likelihood-free inference with toy models or real-life simulation
Implementation of NeurIPS 20 paper: Latent Template Induction with Gumbel-CRFs
Libraries to analyze numerical simulations
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