Improving Neural Additive Models with Bayesian Principles

Improving Neural Additive Models with Bayesian Principles

26 May 2023

Kouroche Bouchiat

Alexander Immer

Vincent Fortuin

Papers citing "Improving Neural Additive Models with Bayesian Principles"

18 / 18 papers shown

Title
Structural Neural Additive Models: Enhanced Interpretable Machine Learning Mattias Luber Anton Thielmann Benjamin Säfken 42 8 0 18 Feb 2023
Why do tree-based models still outperform deep learning on tabular data? Léo Grinsztajn Edouard Oyallon Gaël Varoquaux LMTD 49 361 0 18 Jul 2022
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning Javier Antorán David Janz J. Allingham Erik A. Daxberger Riccardo Barbano Eric T. Nalisnick José Miguel Hernández-Lobato UQCV BDL 54 29 0 17 Jun 2022
Neural Basis Models for Interpretability Filip Radenovic Abhimanyu Dubey D. Mahajan FAtt 70 47 0 27 May 2022
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity Shiyun Xu Zhiqi Bu Pratik Chaudhari Ian Barnett 42 22 0 25 Feb 2022
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 73 305 0 28 Jun 2021
Data augmentation in Bayesian neural networks and the cold posterior effect Seth Nabarro Stoil Ganev Adrià Garriga-Alonso Vincent Fortuin Mark van der Wilk Laurence Aitchison BDL 34 39 0 10 Jun 2021
BNNpriors: A library for Bayesian neural network inference with different prior distributions Vincent Fortuin Adrià Garriga-Alonso Mark van der Wilk Laurence Aitchison BDL UQCV 21 24 0 14 May 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 56 127 0 14 May 2021
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning Alexander Immer Matthias Bauer Vincent Fortuin Gunnar Rätsch Mohammad Emtiyaz Khan BDL UQCV 81 107 0 11 Apr 2021
Bayesian Neural Network Priors Revisited Vincent Fortuin Adrià Garriga-Alonso Sebastian W. Ober F. Wenzel Gunnar Rätsch Richard Turner Mark van der Wilk Laurence Aitchison BDL UQCV 77 140 0 12 Feb 2021
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users Laurent Valentin Jospin Wray Buntine F. Boussaïd Hamid Laga Bennamoun OOD BDL UQCV 39 620 0 14 Jul 2020
lgpr: An interpretable nonparametric method for inferring covariate effects from longitudinal data Juho Timonen Henrik Mannerstrom Aki Vehtari Harri Lähdesmäki 26 14 0 07 Dec 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 56 801 0 07 Feb 2019
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 82 269 0 13 Jun 2018
The Expressive Power of Neural Networks: A View from the Width Zhou Lu Hongming Pu Feicheng Wang Zhiqiang Hu Liwei Wang 46 886 0 08 Sep 2017
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 93 1,500 0 08 Jun 2015
Additive Gaussian Processes David Duvenaud H. Nickisch C. Rasmussen GP 75 329 0 19 Dec 2011

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