additive-models

Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.

Piece-wise exponential Additive Mixed Modeling tools

Interpretable additive models for tabular data: classical GAMs (with REML smoothness selection, inference, shape constraints & diagnostics) plus neural additive models (NAM, NBM, NodeGAM, GPNAM, SIAN, SPAM, and more) for regression, classification, and distributional regression.

A workshop on using generalized additive models and the mgcv package.

A quick reference for how to run many models in R.

Documents that go into methodological detail regarding various statistical procedures.

Official Implementation of ARACHNET: INTERPRETABLE SUB-ARACHNOID SPACE SEGMENTATION USING AN ADDITIVE CONVOLUTIONAL NEURAL NETWORK

PAGER is an efficient genotype encoding strategy designed to improve the detection of non-additive genetic variation in complex trait association studies. PAGER dynamically encodes genetic variants by normalizing mean phenotypic differences between genotype classes.

Python implementations of semiparametric statistical techniques.

İBB'nin İkitelli'de bulunan güneş enerjisi panellerinin gelecek zamanda üretecekleri toplam enerjinin tahmininin yapılmasına ilişkin oluşturulmuş repository.

An introduction to the concepts of Survival Analysis and its implementation in lifelines package for Python.

Pedestrians destination prediction

Piece-wise exponential Additive Mixed Models (PAMMs)

ENSAI : Stage 2A - modèles additifs fonctionnels & déconvolution

Analyses scripts used for Algermissen, J. & den Ouden, H. E. (2024). Pupil dilation reflects effortful action invigoration in overcoming aversive Pavlovian biases. Cognitive, Affective, & Behavioral Neuroscience

A Python Package for a Sparse Additive Boosting Regressor

Basis and penalty matrices in JAX

Bayesian Hierarchical Additive Models

Ferenci Tamás: Simítás, spline-ok, additív modellek

CALM: interpretable by design — accurate locally additive models for tabular data (NeurIPS 2026)