:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Haldar, Swagatam, Stein-Thoeringer, Christoph, Borisov, Vadim
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Quantitative Methods
Online Access:	https://arxiv.org/abs/2410.16109
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multimodal Interpretable Data-Driven Models for Early Prediction of Antimicrobial Multidrug Resistance Using Multivariate Time-Series
by: Martínez-Agüero, Sergio, et al.
Published: (2024)

Interpretable Causal Representation Learning for Biological Data in the Pathway Space
by: de la Fuente, Jesus, et al.
Published: (2025)

Polyformer: a generative framework for thermodynamic modeling of polymeric molecules
by: Valentini, Alessio, et al.
Published: (2026)

Artificial Intelligence for Microbiology and Microbiome Research
by: Wang, Xu-Wen, et al.
Published: (2024)

Distribution Learning for Molecular Regression
by: Shoghi, Nima, et al.
Published: (2024)

Comparative Analysis of Data Preprocessing Methods, Feature Selection Techniques and Machine Learning Models for Improved Classification and Regression Performance on Imbalanced Genetic Data
by: Kaur, Arshmeet, et al.
Published: (2024)

Efficient Approximate Methods for Design of Experiments for Copolymer Engineering
by: Mukhopadhyay, Swagatam
Published: (2024)

Levenshtein Distance Embedding with Poisson Regression for DNA Storage
by: Wei, Xiang, et al.
Published: (2023)

Predicting Drug Solubility Using Different Machine Learning Methods -- Linear Regression Model with Extracted Chemical Features vs Graph Convolutional Neural Network
by: Ho, John, et al.
Published: (2023)

Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data
by: Li, Tinghuan, et al.
Published: (2025)

A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example
by: Choy, Keilung, et al.
Published: (2025)

Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19
by: García-Ordás, María Teresa, et al.
Published: (2024)

Graph-Based Biomarker Discovery and Interpretation for Alzheimer's Disease
by: Khalid, Maryam, et al.
Published: (2024)

Privacy-Preserving Multi-Center Differential Protein Abundance Analysis with FedProt
by: Burankova, Yuliya, et al.
Published: (2024)

Machine Learning Models for the Identification of Cardiovascular Diseases Using UK Biobank Data
by: Islam, Sheikh Mohammed Shariful, et al.
Published: (2024)

Data Augmentation Scheme for Raman Spectra with Highly Correlated Annotations
by: Lange, Christoph, et al.
Published: (2024)

Identification of Capture Phases in Nanopore Protein Sequencing Data Using a Deep Learning Model
by: Martin, Annabelle, et al.
Published: (2025)

A Framework for Feature Discovery in Intracranial Pressure Monitoring Data Using Neural Network Attention
by: Socha, Jonathan D., et al.
Published: (2026)

An Interpretable Neural Network for Vegetation Phenotyping with Visualization of Trait-Based Spectral Features
by: Basener, William, et al.
Published: (2024)

Computational Mapping of Reactive Stroma in Prostate Cancer Yields Interpretable, Prognostic Biomarkers
by: Pleasure, Mara, et al.
Published: (2026)

Global Interpretability via Automated Preprocessing: A Framework Inspired by Psychiatric Questionnaires
by: Strobl, Eric V.
Published: (2026)

Interpretable High-order Knowledge Graph Neural Network for Predicting Synthetic Lethality in Human Cancers
by: Chen, Xuexin, et al.
Published: (2025)

Sequence-Only Prediction of Binding Affinity Changes: A Robust and Interpretable Model for Antibody Engineering
by: Liu, Chen, et al.
Published: (2025)

AIRI: Predicting Retention Indices and their Uncertainties using Artificial Intelligence
by: Geer, Lewis Y., et al.
Published: (2024)

MRC-GAT: A Meta-Relational Copula-Based Graph Attention Network for Interpretable Multimodal Alzheimer's Disease Diagnosis
by: Khalvandi, Fatemeh, et al.
Published: (2026)

Tabular LLMs for Interpretable Few-Shot Alzheimer's Disease Prediction with Multimodal Biomedical Data
by: Kearney, Sophie, et al.
Published: (2026)

Early Prediction of Alzheimer's and Related Dementias: A Machine Learning Approach Utilizing Social Determinants of Health Data
by: Kindo, Bereket, et al.
Published: (2025)

Forecasting Antimicrobial Resistance Trends Using Machine Learning on WHO GLASS Surveillance Data: A Retrieval-Augmented Generation Approach for Policy Decision Support
by: Turja, Md Tanvir Hasan
Published: (2026)

Classifying the Stoichiometry of Virus-like Particles with Interpretable Machine Learning
by: Zhang, Jiayang, et al.
Published: (2025)

Flow Matching for Count Data
by: Wei, Ganchao, et al.
Published: (2026)

Sequence Analysis Using the Bezier Curve
by: Murad, Taslim, et al.
Published: (2025)

Interpretable Multimodal Learning for Tumor Protein-Metal Binding: Progress, Challenges, and Perspectives
by: Liu, Xiaokun, et al.
Published: (2025)

Data Leakage and Redundancy in the LIT-PCBA Benchmark
by: Huang, Amber, et al.
Published: (2025)

VADA: a Data-Driven Simulator for Nanopore Sequencing
by: Niederle, Jonas, et al.
Published: (2024)

Improving Antibody Humanness Prediction using Patent Data
by: Ucar, Talip, et al.
Published: (2024)

Efficient Data Selection for Training Genomic Perturbation Models
by: Panagopoulos, George, et al.
Published: (2025)

Data-driven Discovery of Digital Twins in Biomedical Research
by: Métayer, Clémence, et al.
Published: (2025)

Group Contrastive Learning for Weakly Paired Multimodal Data
by: Gorla, Aditya, et al.
Published: (2026)

Sequential Inference of Hospitalization Electronic Health Records Using Probabilistic Models
by: Kaplan, Alan D., et al.
Published: (2024)

Drug Repurposing Using Deep Embedded Clustering and Graph Neural Networks
by: Delzer, Luke, et al.
Published: (2025)