Additive models

78 papers with code • 0 benchmarks • 0 datasets

This task has no description! Would you like to contribute one?


Use these libraries to find Additive models models and implementations

Most implemented papers

Neural Additive Models: Interpretable Machine Learning with Neural Nets

lemeln/nam NeurIPS 2021

They perform similarly to existing state-of-the-art generalized additive models in accuracy, but are more flexible because they are based on neural nets instead of boosted trees.

Augmenting Interpretable Models with LLMs during Training

csinva/imodelsX 23 Sep 2022

Recent large language models (LLMs) have demonstrated remarkable prediction performance for a growing array of tasks.

Additive Approximations in High Dimensional Nonparametric Regression via the SALSA

kirthevasank/salsa 31 Jan 2016

Between non-additive models which often have large variance and first order additive models which have large bias, there has been little work to exploit the trade-off in the middle via additive models of intermediate order.

Do Not Trust Additive Explanations

ModelOriented/iBreakDown 27 Mar 2019

Explainable Artificial Intelligence (XAI)has received a great deal of attention recently.

InterpretML: A Unified Framework for Machine Learning Interpretability

microsoft/interpret 19 Sep 2019

InterpretML is an open-source Python package which exposes machine learning interpretability algorithms to practitioners and researchers.

Robust Aggregation for Federated Learning

krishnap25/RFA arXiv preprint 2019

We present a robust aggregation approach to make federated learning robust to settings when a fraction of the devices may be sending corrupted updates to the server.

Semi-Structured Distributional Regression -- Extending Structured Additive Models by Arbitrary Deep Neural Networks and Data Modalities

davidruegamer/semi-structured_distributional_regression 13 Feb 2020

We propose a general framework to combine structured regression models and deep neural networks into a unifying network architecture.

GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions

ZebinYang/gaminet 16 Mar 2020

The lack of interpretability is an inevitable problem when using neural network models in real applications.

How Interpretable and Trustworthy are GAMs?

zzzace2000/GAMs 11 Jun 2020

Generalized additive models (GAMs) have become a leading modelclass for interpretable machine learning.

NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning

zzzace2000/nodegam ICLR 2022

Deployment of machine learning models in real high-risk settings (e. g. healthcare) often depends not only on the model's accuracy but also on its fairness, robustness, and interpretability.