Cover Image

BVSIMC: Bayesian Variable Selection-Guided Inductive Matrix Completion for Improved and Interpretable Drug Discovery

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fan, Sijian, Xiong, Liyan, Wang, Dayuan, Cai, Guoshuai, Bai, Ray
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

BiSSLB: Binary Spike-and-Slab Lasso Biclustering
by: Fan, Sijian, et al.
Published: (2026)

Bayesian MI-LASSO for Variable Selection on Multiply-Imputed Data
by: Zou, Jungang, et al.
Published: (2022)

Automating the Selection of Proxy Variables of Unmeasured Confounders
by: Xie, Feng, et al.
Published: (2024)

Mixed Matrix Completion in Complex Survey Sampling under Heterogeneous Missingness
by: Mao, Xiaojun, et al.
Published: (2024)

Matrix Completion via Residual Spectral Matching
by: Chen, Ziyuan, et al.
Published: (2024)

Penalized Generative Variable Selection
by: Wang, Tong, et al.
Published: (2024)

Quantifying predictive uncertainty of aphasia severity in stroke patients with sparse heteroscedastic Bayesian high-dimensional regression
by: Zgodic, Anja, et al.
Published: (2023)

Causal Discovery via Conditional Independence Testing with Proxy Variables
by: Liu, Mingzhou, et al.
Published: (2023)

Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information
by: Ma, Shujie, et al.
Published: (2024)

Distributional Matrix Completion via Nearest Neighbors in the Wasserstein Space
by: Feitelberg, Jacob, et al.
Published: (2024)

Diffusion-Driven High-Dimensional Variable Selection
by: Wang, Minjie, et al.
Published: (2025)

Structured Conformal Inference for Matrix Completion with Applications to Group Recommender Systems
by: Liang, Ziyi, et al.
Published: (2024)

CausalFormer: An Interpretable Transformer for Temporal Causal Discovery
by: Kong, Lingbai, et al.
Published: (2024)

A Meta-Learning Approach to Bayesian Causal Discovery
by: Dhir, Anish, et al.
Published: (2024)

Statistical Inference for Matching Decisions via Matrix Completion under Dependent Missingness
by: Duan, Congyuan, et al.
Published: (2025)

High-Dimensional False Discovery Rate Control for Dependent Variables
by: Machkour, Jasin, et al.
Published: (2024)

Dagma-DCE: Interpretable, Non-Parametric Differentiable Causal Discovery
by: Waxman, Daniel, et al.
Published: (2024)

False Discovery Rate Control via Bayesian Mirror Statistic
by: Molinari, Marco, et al.
Published: (2025)

Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects
by: Bargagli-Stoffi, Falco J., et al.
Published: (2020)

Adaptively-weighted Nearest Neighbors for Matrix Completion
by: Sadhukhan, Tathagata, et al.
Published: (2025)

Inductive Global and Local Manifold Approximation and Projection
by: Kim, Jungeum, et al.
Published: (2024)

Structural Causality-based Generalizable Concept Discovery Models
by: Sinha, Sanchit, et al.
Published: (2024)

Linear Models, Variable Selection, Artificial Intelligence
by: Alrawkan, By Riyadh, et al.
Published: (2026)

Multiple Testing of Linear Forms for Noisy Matrix Completion
by: Ma, Wanteng, et al.
Published: (2023)

Agglomerative Hierarchical Clustering for Selecting Valid Instrumental Variables
by: Apfel, Nicolas, et al.
Published: (2021)

Incorporating Expert Knowledge into Bayesian Causal Discovery of Mixtures of Directed Acyclic Graphs
by: Björkman, Zachris, et al.
Published: (2025)

Score-Based Change-Point Detection and Region Localization for Spatio-Temporal Point Processes
by: Zhou, Wenbin, et al.
Published: (2026)

Stability Selection via Variable Decorrelation
by: Nouraie, Mahdi, et al.
Published: (2025)

Adaptive Selection of the Optimal Strategy to Improve Precision and Power in Randomized Trials
by: Balzer, Laura B., et al.
Published: (2022)

Variable Selection for Comparing High-dimensional Time-Series Data
by: Mitsuzawa, Kensuke, et al.
Published: (2024)

Robust Ultra-High-Dimensional Variable Selection With Correlated Structure Using Group Testing
by: Guo, Wanru, et al.
Published: (2026)

Improving Finite Sample Performance of Causal Discovery by Exploiting Temporal Structure
by: Bang, Christine W, et al.
Published: (2024)

Overcoming Selection Bias in Statistical Studies With Amortized Bayesian Inference
by: Arruda, Jonas, et al.
Published: (2026)

A Graphical Approach to State Variable Selection in Off-policy Learning
by: Andersen, Joakim Blach, et al.
Published: (2025)

Asymptotic Inference for Multi-Stage Stationary Treatment Policy with Variable Selection
by: Gao, Daiqi, et al.
Published: (2023)

Improving Active Learning with a Bayesian Representation of Epistemic Uncertainty
by: Thomas, Jake, et al.
Published: (2024)

Robust Matrix Completion for Discrete Rating-Scale Data: Coping with Fake Profiles in Recommender Systems
by: Archimbaud, Aurore, et al.
Published: (2024)

Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
by: Ye, Shengbin, et al.
Published: (2024)

Latent Network Estimation and Variable Selection for Compositional Data via Variational EM
by: Osborne, Nathan, et al.
Published: (2020)

Robust Variable Selection for High-dimensional Regression with Missing Data and Measurement Errors
by: Zhang, Zhenhao, et al.
Published: (2024)