:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Zeng, Lang, Zhang, Jipeng, Chen, Wei, Ding, Ying
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2307.05881
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Mini-batch Estimation for Deep Cox Models: Statistical Foundations and Practical Guidance
di: Zeng, Lang, et al.
Pubblicazione: (2024)

CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis
di: Alabdallah, Abdallah, et al.
Pubblicazione: (2024)

CoxNTF: A New Approach for Joint Clustering and Prediction in Survival Analysis
di: Fogel, Paul, et al.
Pubblicazione: (2025)

Isotonic Survival Regression: Calibrated Survival Distributions from Deep Cox Models
di: Jain, Anchit, et al.
Pubblicazione: (2026)

FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models
di: Liu, Jiachang, et al.
Pubblicazione: (2024)

Online Survival Analysis: A Bandit Approach under Cox PH Model
di: Xu, Yang, et al.
Pubblicazione: (2026)

CoxKAN: Kolmogorov-Arnold Networks for Interpretable, High-Performance Survival Analysis
di: Knottenbelt, William, et al.
Pubblicazione: (2024)

Structured Learning in Time-dependent Cox Models
di: Wang, Guanbo, et al.
Pubblicazione: (2023)

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

Subgroup Discovery with the Cox Model
di: Izzo, Zachary, et al.
Pubblicazione: (2025)

Extending Cox Proportional Hazards Model with Symbolic Non-Linear Log-Risk Functions for Survival Analysis
di: Cheng, Jiaxiang, et al.
Pubblicazione: (2025)

Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling
di: Musto, Henry, et al.
Pubblicazione: (2024)

Beyond Cox Models: Assessing the Performance of Machine-Learning Methods in Non-Proportional Hazards and Non-Linear Survival Analysis
di: Rossi, Ivan, et al.
Pubblicazione: (2025)

ICODEN: Ordinary Differential Equation Neural Networks for Interval-Censored Data
di: Wang, Haoling, et al.
Pubblicazione: (2026)

Comparison of the Cox proportional hazards model and Random Survival Forest algorithm for predicting patient-specific survival probabilities in clinical trial data
di: Graf, Ricarda, et al.
Pubblicazione: (2025)

Communication-Efficient Distributed Estimation and Inference for Cox's Model
di: Bayle, Pierre, et al.
Pubblicazione: (2023)

Exact Bayesian Gaussian Cox Processes Using Random Integral
di: Tang, Bingjing, et al.
Pubblicazione: (2024)

Addressing Data Heterogeneity in Federated Learning of Cox Proportional Hazards Models
di: Seidi, Navid, et al.
Pubblicazione: (2024)

ICTSurF: Implicit Continuous-Time Survival Functions with Neural Networks
di: Puttanawarut, Chanon, et al.
Pubblicazione: (2023)

DsubCox: A Fast Subsampling Algorithm for Cox Model with Distributed and Massive Survival Data
di: Zhang, Haixiang, et al.
Pubblicazione: (2023)

Square root Cox's survival analysis by the fittest linear and neural networks model
di: van Cutsem, Maxime, et al.
Pubblicazione: (2025)

Beyond Consistency: Inference for the Relative risk functional in Deep Nonparametric Cox Models
di: Ghosal, Sattwik, et al.
Pubblicazione: (2026)

Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
di: Mei, Yongsheng, et al.
Pubblicazione: (2024)

Statistical inference after variable selection in Cox models: A simulation study
di: Schemet, Lena, et al.
Pubblicazione: (2026)

NiSNN-A: Non-iterative Spiking Neural Networks with Attention with Application to Motor Imagery EEG Classification
di: Zhang, Chuhan, et al.
Pubblicazione: (2023)

Uncertainty Quantification With Noise Injection in Neural Networks: A Bayesian Perspective
di: Yuan, Xueqiong, et al.
Pubblicazione: (2025)

Bayesian Cox model with graph-structured variable selection priors for multi-omics biomarker identification
di: Hermansen, Tobias Østmo, et al.
Pubblicazione: (2025)

TINNs: Time-Induced Neural Networks for Solving Time-Dependent PDEs
di: Dai, Chen-Yang, et al.
Pubblicazione: (2026)

Chain-Oriented Objective Logic with Neural Network Feedback Control and Cascade Filtering for Dynamic Multi-DSL Regulation
di: Han, Jipeng
Pubblicazione: (2024)

Federated Learning of Dynamic Bayesian Network via Continuous Optimization from Time Series Data
di: Chen, Jianhong, et al.
Pubblicazione: (2024)

FSTA-SNN:Frequency-based Spatial-Temporal Attention Module for Spiking Neural Networks
di: Yu, Kairong, et al.
Pubblicazione: (2024)

SAFA-SNN: Sparsity-Aware On-Device Few-Shot Class-Incremental Learning with Fast-Adaptive Structure of Spiking Neural Network
di: Zhang, Huijing, et al.
Pubblicazione: (2025)

Kirin: Improving ANN efficiency with SNN Hybridization
di: Wang, Chenyu, et al.
Pubblicazione: (2026)

An Introduction to Deep Survival Analysis Models for Predicting Time-to-Event Outcomes
di: Chen, George H.
Pubblicazione: (2024)

Stabilized Neural Prediction of Potential Outcomes in Continuous Time
di: Hess, Konstantin, et al.
Pubblicazione: (2024)

A Review of Neural Networks in Precipitation Prediction
di: Zeng, Yugong, et al.
Pubblicazione: (2025)

Neural Networks as Surrogate Solvers for Time-Dependent Accretion Disk Dynamics
di: Mao, Shunyuan, et al.
Pubblicazione: (2025)

Low-Rank Adaptation of Evolutionary Deep Neural Networks for Efficient Learning of Time-Dependent PDEs
di: Zhang, Jiahao, et al.
Pubblicazione: (2025)

TrajSurv: Learning Continuous Latent Trajectories from Electronic Health Records for Trustworthy Survival Prediction
di: Zeng, Sihang, et al.
Pubblicazione: (2025)

Ultralight Polarity-Split Neuromorphic SNN for Event-Stream Super-Resolution
di: Xu, Chuanzhi, et al.
Pubblicazione: (2025)