Cover Image

Shared hidden-factor information framework for multiple behavioral tasks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bian, Yuan, Wang, Yuanjia, Guo, Xingche
Format:	Preprint
Published:	2026
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Joint modeling for learning decision-making dynamics in behavioral experiments
by: Bian, Yuan, et al.
Published: (2025)

HMM for Discovering Decision-Making Dynamics Using Reinforcement Learning Experiments
by: Guo, Xingche, et al.
Published: (2024)

Cumulative Marginal Mean Model for Assessing Sequential Effects Using Digital Health Data
by: Guo, Xingche, et al.
Published: (2025)

A Hierarchical Random Effects State-space Model for Modeling Brain Activities from Electroencephalogram Data
by: Guo, Xingche, et al.
Published: (2023)

Anchored Variational Inference for Personalized Sequential Latent-State Models
by: Guo, Xingche
Published: (2026)

Integrative learning of individualized treatment rules from multiple studies with partially overlapping treatments
by: Bian, Yuan, et al.
Published: (2026)

Model Form Identification in High-Dimensional Functional Linear Regressions
by: Guo, Xingche, et al.
Published: (2026)

Variable Selection and Minimax Prediction in High-dimensional Functional Linear Model
by: Guo, Xingche, et al.
Published: (2023)

Semiparametric Analysis of Interval-Censored Data Subject to Inaccurate Diagnoses with A Terminal Event
by: Deng, Yuhao, et al.
Published: (2026)

Multi-level Latent Variable Models for Coheritability Analysis in Electronic Health Records
by: Zhao, Yinjun, et al.
Published: (2025)

An Integrative Approach for Subtyping Mental Disorders Using Multimodal Data
by: Zhao, Yinjun, et al.
Published: (2025)

Mixed-Response State-Space Model for Analyzing Multi-Dimensional Digital Phenotypes
by: Xu, Tianchen, et al.
Published: (2023)

Learning Optimal Dynamic Treatment Regimens Subject to Stagewise Risk Controls
by: Liu, Mochuan, et al.
Published: (2022)

Fusing Individualized Treatment Rules Using Secondary Outcomes
by: Gao, Daiqi, et al.
Published: (2024)

Maximin Learning of Individualized Treatment Effect on Multi-Domain Outcomes
by: Lu, Yuying, et al.
Published: (2026)

Inference on the state process of periodically inhomogeneous hidden Markov models for animal behavior
by: Koslik, Jan-Ole, et al.
Published: (2023)

Debiased Inference for High-Dimensional Regression Models Based on Profile M-Estimation
by: Wang, Yi, et al.
Published: (2025)

Joint estimation of insurance loss development factors using Bayesian hidden Markov models
by: Goold, Conor
Published: (2024)

Multi-task Learning for Heterogeneous Data via Integrating Shared and Task-Specific Encodings
by: Sui, Yang, et al.
Published: (2025)

Dynamic Classification of Latent Disease Progression with Auxiliary Surrogate Labels
by: Cai, Zexi, et al.
Published: (2024)

A semi-supervised framework for diverse multiple hypothesis testing scenarios
by: Freestone, Jack, et al.
Published: (2024)

Predictive posteriors under hidden confounding
by: Meixide, Carlos García, et al.
Published: (2025)

Redefining shared information: a heterogeneity-adaptive framework for meta-analysis
by: Davis, Elizabeth M., et al.
Published: (2026)

Sample size and power determination for assessing overall SNP effects in joint modeling of longitudinal and time-to-event data
by: Bian, Yuan, et al.
Published: (2026)

Using the target trial framework for combining information: external comparator analyses and other applications
by: Ung, Lawson, et al.
Published: (2026)

A general framework for modeling Gaussian process with qualitative and quantitative factors
by: Deng, Linsui, et al.
Published: (2026)

Boosting prediction with data missing not at random
by: Bian, Yuan, et al.
Published: (2025)

Fast and scalable inference in hidden Markov models with Gaussian fields
by: Fischer, Jan-Ole
Published: (2026)

Inference on state occupancy in covariate-driven hidden Markov models
by: Vienken, Maya N., et al.
Published: (2025)

A Markov-switching dynamic matrix factor model for the high-dimensional matrix time series
by: Yuan, Chaofeng, et al.
Published: (2025)

A joint longitudinal-survival framework for dynamic treatment regimen evaluation in sequential multiple assignment randomized trials
by: Chen, Zhengxi, et al.
Published: (2026)

Autoregressive hidden Markov models for high-resolution animal movement data
by: Stoye, Ferdinand V., et al.
Published: (2024)

Bayesian factor zero-inflated Poisson model for multiple grouped count data
by: Kobayashi, Genya, et al.
Published: (2024)

Moving sum procedure for multiple change point detection in large factor models
by: Barigozzi, Matteo, et al.
Published: (2024)

Flexible unimodal density estimation in hidden Markov models
by: Koslik, Jan-Ole, et al.
Published: (2025)

A modelling framework for detecting and leveraging node-level information in Bayesian network inference
by: Xi, Xiaoyue, et al.
Published: (2023)

Conditional GLMMs for reaction times in choice tasks
by: Tejo, Mauricio, et al.
Published: (2025)

Estimating hidden population size from a single respondent-driven sampling survey
by: Yauck, Mamadou, et al.
Published: (2024)

hmmTMB: hidden Markov models with flexible covariate effects in R
by: Michelot, Théo
Published: (2022)

Group integrative dynamic factor models with application to multiple subject brain connectivity
by: Kim, Younghoon, et al.
Published: (2023)