Image de couverture de livre

Variational Deep Survival Machines: Survival Regression with Censored Outcomes

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Wang, Qinxin, Huang, Jiayuan, Li, Junhui, Liu, Jiaming
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Computational Engineering, Finance, and Science
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Linking Across Data Granularity: Fitting Multivariate Hawkes Processes to Partially Interval-Censored Data
par: Calderon, Pio, et autres
Publié: (2021)

Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications?
par: Chen, Rex, et autres
Publié: (2023)

Deep-MacroFin: Informed Equilibrium Neural Network for Continuous Time Economic Models
par: Wu, Yuntao, et autres
Publié: (2024)

Physics-Informed Deep Learning Model for Line-integral Diagnostics Across Fusion Devices
par: Wang, Cong, et autres
Publié: (2024)

Deep Reinforcement Learning in Factor Investment
par: Liu, Junlin
Publié: (2025)

Applications of Machine Learning to Optimizing Polyolefin Manufacturing
par: Sharma, Niket, et autres
Publié: (2024)

Discovering Governing Equations of Geomagnetic Storm Dynamics with Symbolic Regression
par: Markidis, Stefano, et autres
Publié: (2025)

A Simple Baseline for Predicting Events with Auto-Regressive Tabular Transformers
par: Stein, Alex, et autres
Publié: (2024)

Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate
par: Li, Fengpei, et autres
Publié: (2024)

Optimizing Portfolio Management and Risk Assessment in Digital Assets Using Deep Learning for Predictive Analysis
par: Cheng, Qishuo, et autres
Publié: (2024)

Large and Deep Factor Models
par: Kelly, Bryan, et autres
Publié: (2024)

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction
par: Cheng, Yu, et autres
Publié: (2025)

When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks
par: Drinkall, Felix, et autres
Publié: (2025)

Deep Reinforcement Learning for Modelling Protein Complexes
par: Gao, Ziqi, et autres
Publié: (2024)

A Cutting Mechanics-based Machine Learning Modeling Method to Discover Governing Equations of Machining Dynamics
par: Ren, Alisa, et autres
Publié: (2025)

The Role of Deep Learning in Financial Asset Management: A Systematic Review
par: Reis, Pedro, et autres
Publié: (2025)

PIVONet: A Physically-Informed Variational Neuro ODE Model for Efficient Advection-Diffusion Fluid Simulation
par: Cheung, Hei Shing, et autres
Publié: (2026)

Machine Learning based Prediction of Ditching Loads
par: Schwarz, Henning, et autres
Publié: (2024)

Modeling Market States with Clustering and State Machines
par: Oliva, Christian, et autres
Publié: (2025)

A Machine Learning Approach For Bitcoin Forecasting
par: Sossi-Rojas, Stefano, et autres
Publié: (2025)

Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems
par: Yuan, Biao, et autres
Publié: (2024)

Quantum Data Encoding and Variational Algorithms: A Framework for Hybrid Quantum Classical Machine Learning
par: Bose, Bhavna, et autres
Publié: (2025)

Physics-Informed Machine Learning for Smart Additive Manufacturing
par: Sharma, Rahul, et autres
Publié: (2024)

Machine Learning-Assisted Discovery of Flow Reactor Designs
par: Savage, Tom, et autres
Publié: (2023)

Physics-Informed Machine Learning for Grade Prediction in Froth Flotation
par: Nasiri, Mahdi, et autres
Publié: (2024)

Applied Machine Learning to Anomaly Detection in Enterprise Purchase Processes
par: Herreros-Martínez, A., et autres
Publié: (2024)

Using Sentiment and Technical Analysis to Predict Bitcoin with Machine Learning
par: Carosia, Arthur Emanuel de Oliveira
Publié: (2024)

Deep Reinforcement Learning Based Toolpath Generation for Thermal Uniformity in Laser Powder Bed Fusion Process
par: Qin, Mian, et autres
Publié: (2024)

Parametric Nonlinear Volterra Series via Machine Learning: Transonic Aerodynamics
par: Immordino, Gabriele, et autres
Publié: (2024)

Physics-Enhanced Machine Learning: a position paper for dynamical systems investigations
par: Cicirello, Alice
Publié: (2024)

A User-Tunable Machine Learning Framework for Step-Wise Synthesis Planning
par: Prakash, Shivesh, et autres
Publié: (2025)

Addressing the Current Challenges of Quantum Machine Learning through Multi-Chip Ensembles
par: Park, Junghoon Justin, et autres
Publié: (2025)

ML4PhySim : Machine Learning for Physical Simulations Challenge (The airfoil design)
par: Yagoubi, Mouadh, et autres
Publié: (2024)

Physics-Informed Machine Learning Towards A Real-Time Spacecraft Thermal Simulator
par: Oddiraju, Manaswin, et autres
Publié: (2024)

Enhancing Multiscale Simulations with Constitutive Relations-Aware Deep Operator Networks
par: Eivazi, Hamidreza, et autres
Publié: (2024)

Toward Developing Machine-Learning-Aided Tools for the Thermomechanical Monitoring of Nuclear Reactor Components
par: Machado, Luiz Aldeia, et autres
Publié: (2025)

DADO -- Low-Cost Query Strategies for Deep Active Design Optimization
par: Decke, Jens, et autres
Publié: (2023)

Free-form Grid Structure Form Finding based on Machine Learning and Multi-objective Optimisation
par: Meng, Yiping, et autres
Publié: (2024)

ABM-UDE: Developing Surrogates for Epidemic Agent-Based Models via Scientific Machine Learning
par: Murgai, Sharv, et autres
Publié: (2026)

Automated Constitutive Model Discovery by Pairing Sparse Regression Algorithms with Model Selection Criteria
par: Urrea-Quintero, Jorge-Humberto, et autres
Publié: (2025)