:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Parii, Dan, Janssen, Evelyne, Tang, Guangzhi, Kouzinopoulos, Charalampos, Pietrasik, Marcin
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	https://arxiv.org/abs/2504.07638
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Machine Learning for Pattern Detection in Printhead Nozzle Logging
por: Prianikov, Nikola, et al.
Publicado: (2025)

Deep Learning Methods for Detecting Thermal Runaway Events in Battery Production Lines
por: Athanasopoulos, Athanasios, et al.
Publicado: (2025)

Empirical Capacity Model for Self-Attention Neural Networks
por: Härmä, Aki, et al.
Publicado: (2024)

Hardware-Aware YOLO Compression for Low-Power Edge AI on STM32U5 for Weeds Detection in Digital Agriculture
por: Kouzinopoulos, Charalampos S., et al.
Publicado: (2025)

Predictive Modeling of Homeless Service Assignment: A Representation Learning Approach
por: Rahman, Khandker Sadia, et al.
Publicado: (2024)

HybridFL: A Federated Learning Approach for Financial Crime Detection
por: Khan, Afsana, et al.
Publicado: (2026)

Hierarchical Blockmodelling for Knowledge Graphs
por: Pietrasik, Marcin, et al.
Publicado: (2024)

Efficient Deterministic Renewable Energy Forecasting Guided by Multiple-Location Weather Data
por: Symeonidis, Charalampos, et al.
Publicado: (2024)

A Segmented Robot Grasping Perception Neural Network for Edge AI
por: Bröcheler, Casper, et al.
Publicado: (2025)

KANFormer for Predicting Fill Probabilities via Survival Analysis in Limit Order Books
por: Zhong, Jinfeng, et al.
Publicado: (2025)

PathMoG: A Pathway-Centric Modular Graph Neural Network for Multi-Omics Survival Prediction
por: Wang, Di, et al.
Publicado: (2026)

CoLiDR: Concept Learning using Aggregated Disentangled Representations
por: Sinha, Sanchit, et al.
Publicado: (2024)

Neural Additive Experts: Context-Gated Experts for Controllable Model Additivity
por: Xiong, Guangzhi, et al.
Publicado: (2026)

ProtoNAM: Prototypical Neural Additive Models for Interpretable Deep Tabular Learning
por: Xiong, Guangzhi, et al.
Publicado: (2024)

Equitable Survival Prediction: A Fairness-Aware Survival Modeling (FASM) Approach
por: Liu, Mingxuan, et al.
Publicado: (2025)

Toward Conditional Distribution Calibration in Survival Prediction
por: Qi, Shi-ang, et al.
Publicado: (2024)

Understanding Prediction Discrepancies in Machine Learning Classifiers
por: Renard, Xavier, et al.
Publicado: (2021)

EAGLE: Efficient Alignment of Generalized Latent Embeddings for Multimodal Survival Prediction with Interpretable Attribution Analysis
por: Tripathi, Aakash, et al.
Publicado: (2025)

Predicting Survival of Hemodialysis Patients using Federated Learning
por: Raju, Abhiram, et al.
Publicado: (2024)

Unlearning vs. Obfuscation: Are We Truly Removing Knowledge?
por: Sun, Guangzhi, et al.
Publicado: (2025)

Causal Fairness for Survival Analysis
por: Plecko, Drago
Publicado: (2026)

Survival Analysis with Adversarial Regularization
por: Potter, Michael, et al.
Publicado: (2023)

SDPM: Survival Diffusion Probabilistic Model for Continuous-Time Survival Analysis
por: Kirpichenko, Stanislav R., et al.
Publicado: (2026)

GRAFT: Decoupling Ranking and Calibration for Survival Analysis
por: Ashhad, Mohammad, et al.
Publicado: (2026)

Adaptively Pruned Spiking Neural Networks for Energy-Efficient Intracortical Neural Decoding
por: Rivelli, Francesca, et al.
Publicado: (2025)

Energy-Efficient Federated Learning for AIoT using Clustering Methods
por: Pereira, Roberto, et al.
Publicado: (2025)

Are Foundation Models Useful for Bankruptcy Prediction?
por: Kostrzewa, Marcin, et al.
Publicado: (2025)

Automated and Interpretable Survival Analysis from Multimodal Data
por: Malafaia, Mafalda, et al.
Publicado: (2025)

FPBoost: Fully Parametric Gradient Boosting for Survival Analysis
por: Archetti, Alberto, et al.
Publicado: (2024)

Survival Analysis with Machine Learning for Predicting Li-ion Battery Remaining Useful Life
por: Xue, Jingyuan, et al.
Publicado: (2025)

Dual Mixture-of-Experts Framework for Discrete-Time Survival Analysis
por: Lee, Hyeonjun, et al.
Publicado: (2025)

Multimodal Survival Analysis with Locally Deployable Large Language Models
por: Gögl, Moritz, et al.
Publicado: (2026)

Adaptive Transformer Modelling of Density Function for Nonparametric Survival Analysis
por: Zhang, Xin, et al.
Publicado: (2024)

A Mechanistic Explanatory Strategy for XAI
por: Rabiza, Marcin
Publicado: (2024)

KAPLAN: Kolmogorov-Arnold Prognostic Learnable Activation Networks for Survival Analysis
por: Logothetis, Stelios Boulitsakis, et al.
Publicado: (2026)

TripleSurv: Triplet Time-adaptive Coordinate Loss for Survival Analysis
por: Zhang, Liwen, et al.
Publicado: (2024)

TabSurv: Adapting Modern Tabular Neural Networks to Survival Analysis
por: Kirpichenko, Stanislav, et al.
Publicado: (2026)

A Multimodal Object-level Contrast Learning Method for Cancer Survival Risk Prediction
por: Yang, Zekang, et al.
Publicado: (2024)

Deep Neural Networks for Predicting Recurrence and Survival in Patients with Esophageal Cancer After Surgery
por: Zheng, Yuhan, et al.
Publicado: (2024)

Survival Analysis Revisited: Understanding and Unifying Poisson, Exponential, and Cox Models in Fall Risk Analysis
por: Chen, Tianhua
Publicado: (2025)