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

Title
Comparison of generalised additive models and neural networks in applications: A systematic review Jessica Doohan Lucas Kook Kevin Burke 40 0 0 28 Oct 2025
Anchor-MoE: A Mean-Anchored Mixture of Experts For Probabilistic Regression Baozhuo Su Zhengxian Qu MoE 60 0 0 22 Aug 2025
Beyond Black-Box Predictions: Identifying Marginal Feature Effects in Tabular Transformer Networks Anton Thielmann Arik Reuter Benjamin Saefken LMTD 359 0 0 11 Apr 2025
Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting Simon Hirsch 530 2 0 03 Apr 2025
A Functional Extension of Semi-Structured NetworksNeural Information Processing Systems (NeurIPS), 2024 David Rügamer Bernard X. W. Liew Zainab Altai Almond Stöcker 124 0 0 07 Oct 2024
How Inverse Conditional Flows Can Serve as a Substitute for Distributional RegressionConference on Uncertainty in Artificial Intelligence (UAI), 2024 Lucas Kook Chris Kolb Philipp Schiele Daniel Dold Marcel Arpogaus ... Philipp F. M. Baumann Philipp Kopper Tobias Pielok Emilio Dorigatti David Rügamer BDL AI4TS 311 2 0 08 May 2024
Generalizing Orthogonalization for Models with Non-LinearitiesInternational Conference on Machine Learning (ICML), 2024 David Rügamer Chris Kolb Tobias Weber Lucas Kook Thomas Nagler 193 1 0 03 May 2024
Reflectance Estimation for Proximity Sensing by Vision-Language Models: Utilizing Distributional Semantics for Low-Level Cognition in Robotics Masashi Osada G. A. G. Ricardez Yosuke Suzuki Tadahiro Taniguchi 209 4 0 11 Apr 2024
Neural Additive Image Model: Interpretation through Interpolation Arik Reuter Anton Thielmann Benjamin Saefken DiffM 329 2 0 06 Mar 2024
Bayesian Semi-structured Subspace InferenceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Daniel Dold David Rügamer Beate Sick Oliver Durr BDL 128 1 0 23 Jan 2024
Post-hoc Orthogonalization for Mitigation of Protected Feature Bias in CXR Embeddings Tobias Weber Michael Ingrisch B. Bischl David Rügamer CML 194 1 0 02 Nov 2023
A New PHO-rmula for Improved Performance of Semi-Structured NetworksInternational Conference on Machine Learning (ICML), 2023 David Rügamer 130 11 0 01 Jun 2023
Deep Learning for Survival Analysis: A ReviewArtificial Intelligence Review (AIR), 2023 S. Wiegrebe Philipp Kopper R. Sonabend B. Bischl Andreas Bender 284 128 0 24 May 2023
The Deep Promotion Time Cure ModelIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023 Victor Medina-Olivares Stefan Lessmann Nadja Klein 138 1 0 19 May 2023
mixdistreg: An R Package for Fitting Mixture of Experts Distributional Regression with Adaptive First-order Methods David Rügamer 156 1 0 04 Feb 2023
Estimating Conditional Distributions with Neural Networks using R package deeptrafoJournal of Statistical Software (JSS), 2022 Lucas Kook Philipp F. M. Baumann Oliver Durr Beate Sick David Rügamer 204 6 0 24 Nov 2022
Mixture of Experts Distributional Regression: Implementation Using Robust Estimation with Adaptive First-order MethodsAStA Advances in Statistical Analysis (AStA), 2022 David Rügamer Florian Pfisterer B. Bischl Bettina Grün 87 4 0 17 Nov 2022
A review of predictive uncertainty estimation with machine learningArtificial Intelligence Review (Artif Intell Rev), 2022 Hristos Tyralis Georgia Papacharalampous UD UQCV 319 71 0 17 Sep 2022
A Statistical-Modelling Approach to Feedforward Neural Network Model SelectionStatistical Modelling (SM), 2022 Andrew McInerney Kevin Burke 367 4 0 09 Jul 2022