Bayesian Deep Net GLM and GLMM

Bayesian Deep Net GLM and GLMM

25 May 2018

Papers citing "Bayesian Deep Net GLM and GLMM"

13 / 13 papers shown

Title
Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods Andrej Tschalzev Paul Nitschke Lukas Kirchdorfer Stefan Lüdtke Christian Bartelt Heiner Stuckenschmidt 29 0 0 01 Jul 2024
Scalable Bayesian inference for the generalized linear mixed model S. Berchuck Felipe A. Medeiros Sayan Mukherjee Andrea Agazzi 29 0 0 05 Mar 2024
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML OOD 68 2 0 16 Oct 2023
Particle Mean Field Variational Bayes Minh-Ngoc Tran Paco Tseng Robert Kohn 32 3 0 24 Mar 2023
Training Normalizing Flows from Dependent Data Matthias Kirchler C. Lippert Marius Kloft TPM 21 2 0 29 Sep 2022
Integrating Random Effects in Deep Neural Networks Giora Simchoni Saharon Rosset BDL AI4CE 27 21 0 07 Jun 2022
Nys-Newton: Nyström-Approximated Curvature for Stochastic Optimization Dinesh Singh Hardik Tankaria M. Yamada ODL 42 2 0 16 Oct 2021
LocalGLMnet: interpretable deep learning for tabular data Ronald Richman M. Wüthrich LMTD FAtt 20 27 0 23 Jul 2021
A practical tutorial on Variational Bayes Minh-Ngoc Tran Trong-Nghia Nguyen Viet-Hung Dao BDL 29 38 0 01 Mar 2021
Assessment and adjustment of approximate inference algorithms using the law of total variance Xue Yu David J. Nott Minh-Ngoc Tran Nadja Klein 14 15 0 20 Nov 2019
Deep Integro-Difference Equation Models for Spatio-Temporal Forecasting A. Zammit‐Mangion C. Wikle 8 47 0 29 Oct 2019
Marginally-calibrated deep distributional regression Nadja Klein David J. Nott M. Smith UQCV 32 14 0 26 Aug 2019
Variational Particle Approximations A. Saeedi Tejas D. Kulkarni Vikash K. Mansinghka S. Gershman 82 60 0 24 Feb 2014