Imagen de Portada

Exploring Cumulative Effects in Survival Data Using Deep Learning Networks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Yang, Kang-Chung, Yuan, Shinsheng
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Flexible Deep Neural Networks for Partially Linear Survival Data: Estimation and Survival Inference
por: Arie, Asaf Ben, et al.
Publicado: (2025)

Learning Beyond the Gaussian Data: Learning Dynamics of Neural Networks on an Expressive and Cumulant-Controllable Data Model
por: Ure, Onat, et al.
Publicado: (2026)

Fréchet Cumulative Covariance Net for Deep Nonlinear Sufficient Dimension Reduction with Random Objects
por: Yuan, Hang, et al.
Publicado: (2025)

Synthetic Survival Data Generation for Heart Failure Prognosis Using Deep Generative Models
por: Puttanawarut, Chanon, et al.
Publicado: (2025)

Deep Learning for Survival Analysis: A Review
por: Wiegrebe, Simon, et al.
Publicado: (2023)

Tuning Learning Rates with the Cumulative-Learning Constant
por: Faraj, Nathan
Publicado: (2025)

Gradient-based Explanations for Deep Learning Survival Models
por: Langbein, Sophie Hanna, et al.
Publicado: (2025)

Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback
por: Shen, Wei, et al.
Publicado: (2025)

Explore Briefly, Then Decide: Mitigating LLM Overthinking via Cumulative Entropy Regulation
por: Bin, Yi, et al.
Publicado: (2025)

Deep Partially Linear Transformation Model for Right-Censored Survival Data
por: Yin, Junkai, et al.
Publicado: (2024)

Exploring the Feasibility of Deep Learning Models for Long-term Disease Prediction: A Case Study for Wheat Yellow Rust in England
por: Yuan, Zhipeng, et al.
Publicado: (2025)

Deep Survival Analysis for Competing Risk Modeling with Functional Covariates and Missing Data Imputation
por: Gao, Penglei, et al.
Publicado: (2025)

Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee
por: Chen, George H.
Publicado: (2022)

Learning Guarantee of Reward Modeling Using Deep Neural Networks
por: Luo, Yuanhang, et al.
Publicado: (2025)

Cumulative Meta-Learning from Active Learning Queries for Robustness to Spurious Correlations
por: Chew, Kin Whye, et al.
Publicado: (2026)

Multimodal Integration of Longitudinal Noninvasive Diagnostics for Survival Prediction in Immunotherapy Using Deep Learning
por: Yeghaian, Melda, et al.
Publicado: (2024)

Deep Survival Analysis in Multimodal Medical Data: A Parametric and Probabilistic Approach with Competing Risks
por: Garrido, Alba, et al.
Publicado: (2025)

Estimating Heterogeneous Causal Effect on Networks via Orthogonal Learning
por: Wu, Yuanchen, et al.
Publicado: (2025)

SurvReLU: Inherently Interpretable Survival Analysis via Deep ReLU Networks
por: Sun, Xiaotong, et al.
Publicado: (2024)

Exploring Federated Deep Learning for Standardising Naming Conventions in Radiotherapy Data
por: Haidar, Ali, et al.
Publicado: (2024)

Learning Rate Optimization for Deep Neural Networks Using Lipschitz Bandits
por: Priyanka, Padma, et al.
Publicado: (2024)

Policy Gradients for Cumulative Prospect Theory in Reinforcement Learning
por: Lepel, Olivier, et al.
Publicado: (2024)

QComp: A QSAR-Based Data Completion Framework for Drug Discovery
por: Yang, Bingjia, et al.
Publicado: (2024)

Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data
por: Frauen, Dennis, et al.
Publicado: (2025)

Identification and Estimation of Simultaneous Equation Models Using Higher-Order Cumulant Restrictions
por: Jiang, Ziyu
Publicado: (2025)

Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants
por: Tramontano, Daniele, et al.
Publicado: (2025)

Explore the Ideology of Deep Learning in ENSO Forecasts
por: Gan, Yanhai, et al.
Publicado: (2026)

Adaptive Data Exploitation in Deep Reinforcement Learning
por: Yuan, Mingqi, et al.
Publicado: (2025)

Horizontal and Vertical Federated Causal Structure Learning via Higher-order Cumulants
por: Chen, Wei, et al.
Publicado: (2025)

Cumulative Learning Rate Adaptation: Revisiting Path-Based Schedules for SGD and Adam
por: Atamna, Asma, et al.
Publicado: (2025)

Survival In-Context: Amortized Bayesian Survival Analysis via Prior-Fitted Networks
por: Seletkov, Dmitrii, et al.
Publicado: (2026)

Exploring Factors Affecting Pedestrian Crash Severity Using TabNet: A Deep Learning Approach
por: Rafe, Amir, et al.
Publicado: (2023)

Structural Connectome Harmonization Using Deep Learning: The Strength of Graph Neural Networks
por: Patel, Jagruti, et al.
Publicado: (2025)

Deep End-to-End Survival Analysis with Temporal Consistency
por: Vieyra, Mariana Vargas, et al.
Publicado: (2024)

Deep Learning-Based Survival Analysis with Copula-Based Activation Functions for Multivariate Response Prediction
por: Kim, Jong-Min, et al.
Publicado: (2025)

Adaptive Data Harvesting for Efficient Neural Network Learning with Universal Constraints
por: Kang, Siteng, et al.
Publicado: (2026)

Densely Distilling Cumulative Knowledge for Continual Learning
por: Shi, Zenglin, et al.
Publicado: (2024)

Usage-Specific Survival Modeling Based on Operational Data and Neural Networks
por: Holmer, Olov, et al.
Publicado: (2024)

Experience-Efficient Model-Free Deep Reinforcement Learning Using Pre-Training
por: Yang, Ruoxing
Publicado: (2025)

Analysis of Financial Risk Behavior Prediction Using Deep Learning and Big Data Algorithms
por: Yang, Haowei, et al.
Publicado: (2024)