Buchumschlag

Cohort-attention Evaluation Metric against Tied Data: Studying Performance of Classification Models in Cancer Detection

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Wei, Longfei, Sheng, Fang, Zhang, Jianfei
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Machine Learning Computational Engineering, Finance, and Science
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Scale-Equivariant Generative Forecasting: Weight-Tied Dilated Convolutions, Wavelet Scattering Inputs, and Spectral-Consistency Training for Self-Similar Time Series
von: Morandi, Andrea
Veröffentlicht: (2026)

RGDA-DDI: Residual graph attention network and dual-attention based framework for drug-drug interaction prediction
von: Zhou, Changjian, et al.
Veröffentlicht: (2024)

Cross-attention-based bipartite graph neural network for coupled nodal and elemental field prediction in large-deformation sheet material forming
von: Zhao, Yingxue, et al.
Veröffentlicht: (2026)

EP-GAT: Energy-based Parallel Graph Attention Neural Network for Stock Trend Classification
von: Jiang, Zhuodong, et al.
Veröffentlicht: (2025)

Multi-task Meta Label Correction for Time Series Prediction
von: Yang, Luxuan, et al.
Veröffentlicht: (2023)

Constraining Generative Models for Engineering Design with Negative Data
von: Regenwetter, Lyle, et al.
Veröffentlicht: (2023)

GUST: Quantifying Free-Form Geometric Uncertainty of Metamaterials Using Small Data
von: Zheng, Jiahui, et al.
Veröffentlicht: (2025)

Probabilistic Surrogate Model for Accelerating the Design of Electric Vehicle Battery Enclosures for Crash Performance
von: Shaikh, Shadab Anwar, et al.
Veröffentlicht: (2024)

SparseST: Exploiting Data Sparsity in Spatiotemporal Modeling and Prediction
von: Wu, Junfeng, et al.
Veröffentlicht: (2025)

Evaluating the Efficacy of Instance Incremental vs. Batch Learning in Delayed Label Environments: An Empirical Study on Tabular Data Streaming for Fraud Detection
von: Amekoe, Kodjo Mawuena, et al.
Veröffentlicht: (2024)

Latent Generative Modeling of Random Fields from Limited Training Data
von: Warner, James E., et al.
Veröffentlicht: (2025)

Unified Network-Based Representation of BIM Models for Embedding Semantic, Spatial, and Topological Data
von: Han, Jin, et al.
Veröffentlicht: (2025)

Large and Deep Factor Models
von: Kelly, Bryan, et al.
Veröffentlicht: (2024)

MemKD: Memory-Discrepancy Knowledge Distillation for Efficient Time Series Classification
von: Udayangani, Nilushika, et al.
Veröffentlicht: (2026)

Heterogenous Multi-Source Data Fusion Through Input Mapping and Latent Variable Gaussian Process
von: Comlek, Yigitcan, et al.
Veröffentlicht: (2024)

A Data-Efficient Sequential Learning Framework for Melt Pool Defect Classification in Laser Powder Bed Fusion
von: Raihan, Ahmed Shoyeb, et al.
Veröffentlicht: (2024)

UAMM: Price-oracle based Automated Market Maker
von: Im, Daniel Jiwoong, et al.
Veröffentlicht: (2023)

Two-Stage Surrogate Modeling for Data-Driven Design Optimization with Application to Composite Microstructure Generation
von: Pourkamali-Anaraki, Farhad, et al.
Veröffentlicht: (2024)

Data-Driven, Parameterized Reduced-order Models for Predicting Distortion in Metal 3D Printing
von: Deo, Indu Kant, et al.
Veröffentlicht: (2024)

Data-Driven Modeling of an Unsaturated Bentonite Buffer Model Test Under High Temperatures Using an Enhanced Axisymmetric Reproducing Kernel Particle Method
von: Baek, Jonghyuk, et al.
Veröffentlicht: (2023)

Bridging Equilibrium and Kinetics Prediction with a Data-Weighted Neural Network Model of Methane Steam Reforming
von: Pizoń, Zofia, et al.
Veröffentlicht: (2025)

Automated Flow Pattern Classification in Multi-phase Systems Using AI and Capacitance Sensing Techniques
von: Ran, Nian, et al.
Veröffentlicht: (2025)

Utilizing GANs for Fraud Detection: Model Training with Synthetic Transaction Data
von: Zhu, Mengran, et al.
Veröffentlicht: (2024)

Privacy-Preserving Generation Fraud Detection for Distributed Photovoltaic Systems: A Solar Irradiance-Fused Federated Learning Framework
von: Chen, Xiaolu, et al.
Veröffentlicht: (2026)

SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation
von: Wu, Qilong, et al.
Veröffentlicht: (2024)

Are Large Language Models Dynamic Treatment Planners? An In Silico Study from a Prior Knowledge Injection Angle
von: Luo, Zhiyao, et al.
Veröffentlicht: (2025)

On the Detection of Internal Defects in Structured Media
von: Ong, Bryl Nico M., et al.
Veröffentlicht: (2025)

Linking Across Data Granularity: Fitting Multivariate Hawkes Processes to Partially Interval-Censored Data
von: Calderon, Pio, et al.
Veröffentlicht: (2021)

Physics-Informed Geometric Operators to Support Surrogate, Dimension Reduction and Generative Models for Engineering Design
von: Khan, Shahroz, et al.
Veröffentlicht: (2024)

FinTeam: A Multi-Agent Collaborative Intelligence System for Comprehensive Financial Scenarios
von: Wu, Yingqian, et al.
Veröffentlicht: (2025)

Calibrating Scientific Foundation Models with Inference-Time Stochastic Attention
von: Yadav, Akash, et al.
Veröffentlicht: (2026)

Applied Machine Learning to Anomaly Detection in Enterprise Purchase Processes
von: Herreros-Martínez, A., et al.
Veröffentlicht: (2024)

Operator Learning for Reconstructing Flow Fields from Sparse Measurements: a Language Model Approach
von: Zhang, Qian, et al.
Veröffentlicht: (2026)

Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications?
von: Chen, Rex, et al.
Veröffentlicht: (2023)

Semantic-Enhanced Time-Series Forecasting via Large Language Models
von: Liu, Hao, et al.
Veröffentlicht: (2025)

Privacy-Preserving Federated Fraud Detection in Payment Transactions with NVIDIA FLARE
von: Roth, Holger R., et al.
Veröffentlicht: (2026)

Detection of anomalies in cow activity using wavelet transform based features
von: Guien, Valentin, et al.
Veröffentlicht: (2025)

Deep Reinforcement Learning for Modelling Protein Complexes
von: Gao, Ziqi, et al.
Veröffentlicht: (2024)

Predicting Filter Medium Performances in Chamber Filter Presses with Digital Twins Using Neural Network Technologies
von: Teutscher, Dennis, et al.
Veröffentlicht: (2025)

R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
von: Li, Yuante, et al.
Veröffentlicht: (2025)