Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

TAPAS - Translational Algorithms for Psychiatry-Advancing Science

Train and visualize Hierarchical Attention Networks

The base NIMBLE package for R

Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg

Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview questions on clustering are also added in the end.

[IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"

DrugHIVE: Structure-based drug design with a deep hierarchical generative model

PyTorch Implementation of Deep Hierarchical Classification for Category Prediction in E-commerce System

This is project page for the paper "RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior". Paper link: https://arxiv.org/abs/2010.00029

Code for A Hierarchical Model for Data-to-Text Generation (Rebuffel, Soulier, Scoutheeten, Gallinari; ECIR 2020)

My solutions to the exercises in "Data Analysis Using Regression and Multilevel/Hierarchical Models" by Andrew Gelman and Jennifer Hill

Hierarchical Attention Networks for Document Classification in Keras

Recursively tracks changes within a view model no matter how deeply nested the observables are or whether they are nested within dynamically created array elements.

Message Passing Attention Networks for Document Understanding

[KDD 2020] Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding

[ECCV2024] PartGLEE: A Foundation Model for Recognizing and Parsing Any Objects

Code for the paper "Fine-Grained Entity Typing in Hyperbolic Space"

Fit models to data from unmarked animals using Stan. Uses a similar interface to the R package 'unmarked', while providing the advantages of Bayesian inference and allowing estimation of random effects.

[WWW 2023] The source code of "Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning"