hierarchical-models

There are 157 repositories under hierarchical-models topic.

  • JWarmenhoven/DBDA-python

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

    Language:Jupyter Notebook6682911263

  • translationalneuromodeling/tapas

    TAPAS - Translational Algorithms for Psychiatry-Advancing Science

    Language:MATLAB2082323187

  • minqi/hnatt

    Train and visualize Hierarchical Attention Networks

    Language:Python20312835

  • nimble-dev/nimble

    The base NIMBLE package for R

    Language:C++1511973321

  • jonsedar/pymc3_vs_pystan

    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

    Language:Jupyter Notebook1277042

  • CRIPAC-DIG/H-GCN

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

    Language:Python1155926

  • sandipanpaul21/Clustering-in-Python

    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.

    Language:Jupyter Notebook1006045

  • hongyehu/RG-Flow

    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

    Language:Python833111

  • Ugenteraan/Deep_Hierarchical_Classification

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

    Language:Python824720

  • KaijuML/data-to-text-hierarchical

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

    Language:Python8061130

  • IamGianluca/arm

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

    Language:Jupyter Notebook768047

  • ZiadJ/knockoutjs-reactor

    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.

    Language:JavaScript74123723

  • arunarn2/HierarchicalAttentionNetworks

    Hierarchical Attention Networks for Document Classification in Keras

    Language:Python723428

  • giannisnik/mpad

    Message Passing Attention Networks for Document Understanding

    Language:Python594317

  • yumeng5/JoSH

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

    Language:C58496

  • kenkellner/ubms

    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.

    Language:R359528

  • nlpAThits/figet-hyperbolic-space

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

    Language:Python35631

  • Sshanu/Hierarchical-Word-Sense-Disambiguation-using-WordNet-Senses

    Word Sense Disambiguation using Word Specific models, All word models and Hierarchical models in Tensorflow

    Language:Jupyter Notebook33416

  • VSainteuf/metric-guided-prototypes-pytorch

    PyTorch implementation of Metric-Guided Prototype Learning for hierarchical classification.

    Language:Jupyter Notebook26334

  • cran-task-views/MixedModels

    CRAN Task View: Mixed, Multilevel, and Hierarchical Models in R

    Language:R257468

  • CRIPAC-DIG/HGLS

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

    Language:Python23135

  • LCBC-UiO/galamm

    An R package for estimating generalized additive mixed models with latent variables

    Language:C++223562

  • hanjq17/EGHN

    [NeurIPS 2022] The implementation for the paper "Equivariant Graph Hierarchy-Based Neural Networks".

    Language:Python21313

  • andreaskapou/scMET

    Bayesian modelling of DNA methylation heterogeneity at single-cell resolution

    Language:R19242

  • cbg-ethz/scDEF

    Deep exponential families for single-cell data.

    Language:Python18400

  • XL2248/VHM

    Code for the ACL2022 main conference paper "A Variational Hierarchical Model for Neural Cross-Lingual Summarization"

    Language:Python18232

  • mkearney/tidymlm

    🎓 Tidy multilevel modeling tools for academics

    Language:R1740

  • brettkromkamp/typed-tree

    TypedTree provides a tree data structure that allows adding type information to both nodes and edges; useful for visualisation purposes

    Language:Python16221

  • hanyas/mimo

    A toolbox for inference of mixture models

    Language:Python16204

  • MonarchStore/monarchs

    A hierarchical, NoSQL, in-memory data store with a RESTful API

    Language:Go14526

  • DoseResponse/medrc

    Hierarchical dose-response models in R

    Language:R12491

  • akash18tripathi/MAGNET-Multi-Label-Text-Classi-cation-using-Attention-based-Graph-Neural-Network

    This GitHub repository provides an implementation of the paper "MAGNET: Multi-Label Text Classification using Attention-based Graph Neural Network" . MAGNET is a state-of-the-art approach for multi-label text classification, leveraging the power of graph neural networks (GNNs) and attention mechanisms.

    Language:Jupyter Notebook11200

  • mdnunez/mcntoolbox

    The Mathematical Cognitive Neuroscience Toolbox (mcntoolbox). Code associated with the publication "How attention influences perceptual decision making: Single-trial EEG correlates of drift-diffusion model parameters."

    Language:MATLAB11414

  • NJdevPro/Closure-Table

    An implementation of the closure table pattern in Python + SQL

    Language:Python11202

  • smsharma/hierarchical-inference

    Hierarchical neural implicit inference over event ensembles. Code repository associated with https://arxiv.org/abs/2306.12584.

    Language:Jupyter Notebook11210

  • wangruinju/Double-Fusion

    A bayesian approach to examining default mode network functional connectivity and cognitive performance in major depressive disorder

    Language:Python11402