Cover Image

Semi-Supervised Hierarchical Multi-Label Classifier Based on Local Information

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Serrano-Pérez, Jonathan, Sucar, L. Enrique
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Quantitative Methods
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Application of Machine Learning Algorithms in Classifying Postoperative Success in Metabolic Bariatric Surgery: A Comprehensive Study
by: Benítez-Andrades, José Alberto, et al.
Published: (2024)

Hierarchical Contrastive Learning for Multi-Domain Protein-Ligand Binding
by: Zhang, Shuo, et al.
Published: (2026)

Hierarchical Molecular Representation Learning via Fragment-Based Self-Supervised Embedding Prediction
by: Wu, Jiele, et al.
Published: (2026)

Development of Machine Learning Classifiers for Blood-based Diagnosis and Prognosis of Suspected Acute Infections and Sepsis
by: Buturovic, Ljubomir, et al.
Published: (2024)

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

Molecular Odor Prediction Based on Multi-Feature Graph Attention Networks
by: Xie, HongXin, et al.
Published: (2025)

Donor-Aware scRNA-seq Benchmarks for IBD Classification
by: Muhire, Jonathan
Published: (2026)

scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data
by: Ovcharenko, Olga, et al.
Published: (2025)

Quantifying Heterogeneous Ecosystem Services With Multi-Label Soft Classification
by: Tian, Zhihui, et al.
Published: (2024)

Multi-Integration of Labels across Categories for Component Identification (MILCCI)
by: Mudrik, Noga, et al.
Published: (2026)

Bayesian and Convolutional Networks for Hierarchical Morphological Classification of Galaxies
by: Serrano-Pérez, Jonathan, et al.
Published: (2024)

PLA-SGCN: Protein-Ligand Binding Affinity Prediction by Integrating Similar Pairs and Semi-supervised Graph Convolutional Network
by: Abbasi, Karim, et al.
Published: (2024)

HiGraphDTI: Hierarchical Graph Representation Learning for Drug-Target Interaction Prediction
by: Liu, Bin, et al.
Published: (2024)

Transformer-Based Multi-Modal Temporal Embeddings for Explainable Metabolic Phenotyping in Type 1 Diabetes
by: Khokhar, Pir Bakhsh, et al.
Published: (2026)

Peptide-GPT: Generative Design of Peptides using Generative Pre-trained Transformers and Bio-informatic Supervision
by: Shah, Aayush, et al.
Published: (2024)

Prenatal Stress Detection from Electrocardiography Using Self-Supervised Deep Learning: Development and External Validation
by: Frasch, Martin G., et al.
Published: (2026)

Med-Real2Sim: Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning
by: Kuang, Keying, et al.
Published: (2024)

Towards AI-Based Precision Oncology: A Machine Learning Framework for Personalized Counterfactual Treatment Suggestions based on Multi-Omics Data
by: Schürch, Manuel, et al.
Published: (2024)

Adapting Differential Molecular Representation with Hierarchical Prompts for Multi-label Property Prediction
by: Kang, Linjia, et al.
Published: (2024)

Hierarchical novel class discovery for single-cell transcriptomic profiles
by: Senoussi, Malek, et al.
Published: (2024)

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning
by: Chen, Shaohan, et al.
Published: (2024)

Improving Paratope and Epitope Prediction by Multi-Modal Contrastive Learning and Interaction Informativeness Estimation
by: Wang, Zhiwei, et al.
Published: (2024)

Escaping Local Optima in the Waddington Landscape: A Two-Stage TRPO-PPO Approach for Single-Cell Perturbation Analysis
by: Boabang, Francis, et al.
Published: (2025)

Improving Prediction of Need for Mechanical Ventilation using Cross-Attention
by: Mohanty, Anwesh, et al.
Published: (2024)

Generative Distribution Embeddings: Lifting autoencoders to the space of distributions for multiscale representation learning
by: Fishman, Nic, et al.
Published: (2025)

FPLIER: Federated Pathway-Level Information Extractor
by: Malpetti, Daniele, et al.
Published: (2026)

Exploring the Generalization of Cancer Clinical Trial Eligibility Classifiers Across Diseases
by: Yang, Yumeng, et al.
Published: (2024)

RetroDiff: Retrosynthesis as Multi-stage Distribution Interpolation
by: Wang, Yiming, et al.
Published: (2023)

Geometric Self-Supervised Pretraining on 3D Protein Structures using Subgraphs
by: Chatzianastasis, Michail, et al.
Published: (2024)

CardiGraphormer: Unveiling the Power of Self-Supervised Learning in Revolutionizing Drug Discovery
by: Gupta, Abhijit
Published: (2023)

BaMANI: Bayesian Multi-Algorithm causal Network Inference
by: Latifizadeh, Habibolla, et al.
Published: (2025)

Transforming Multi-Omics Integration with GANs: Applications in Alzheimer's and Cancer
by: Reza, Md Selim, et al.
Published: (2025)

Multi-Modality Representation Learning for Antibody-Antigen Interactions Prediction
by: Guo, Peijin, et al.
Published: (2025)

Is Sequence Information All You Need for Bayesian Optimization of Antibodies?
by: Ober, Sebastian W., et al.
Published: (2025)

Curiosity as a Self-Supervised Method to Improve Exploration in De novo Drug Design
by: Chadi, Mohamed-Amine, et al.
Published: (2023)

Medication Recommendation via Dual Molecular Modalities and Multi-Step Enhancement
by: Mu, Shi, et al.
Published: (2024)

Accelerated Discovery of Cryoprotectant Cocktails via Multi-Objective Bayesian Optimization
by: Emerson, Daniel, et al.
Published: (2026)

Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Information
by: Jayagopal, Aishwarya, et al.
Published: (2024)

LAMP-PRo: Label-aware Attention for Multi-label Prediction of DNA- and RNA-binding Proteins using Protein Language Models
by: Ghosh, Nimisha, et al.
Published: (2025)

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