Copertina

Quantum Amplitude Estimation for Catastrophe Insurance Tail-Risk Pricing: Empirical Convergence and NISQ Noise Analysis

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Kirke, Alexis
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Applications Artificial Intelligence Computational Engineering, Finance, and Science Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

ML-Based Bidding Price Prediction for Pay-As-Bid Ancillary Services Markets: A Use Case in the German Control Reserve Market
di: Bezold, Vincent, et al.
Pubblicazione: (2025)

InferenceEvolve: Towards Automated Causal Effect Estimators through Self-Evolving AI
di: Wang, Can, et al.
Pubblicazione: (2026)

A Framework for Digital Asset Risks with Insurance Applications
di: Li, Zhengming, et al.
Pubblicazione: (2024)

Bitcoin Price Prediction using Machine Learning and Combinatorial Fusion Analysis
di: Wu, Yuanhong, et al.
Pubblicazione: (2026)

Hidformer: Transformer-Style Neural Network in Stock Price Forecasting
di: Szydłowski, Kamil Ł., et al.
Pubblicazione: (2024)

Modeling the Evolutionary Trends in Corporate ESG Reporting: A Study based on Knowledge Management Model
di: Xia, Ziyuan, et al.
Pubblicazione: (2023)

Fire-EnSF: Wildfire Spread Data Assimilation using Ensemble Score Filter
di: Shi, Hongzheng, et al.
Pubblicazione: (2025)

Dynamic causal discovery in Alzheimer's disease through latent pseudotime modelling
di: Glazman, Natalia, et al.
Pubblicazione: (2025)

Use ADAS Data to Predict Near-Miss Events: A Group-Based Zero-Inflated Poisson Approach
di: Zhang, Xinbo, et al.
Pubblicazione: (2025)

Digital Twins and Civil Engineering Phases: Reorienting Adoption Strategies
di: Adebiyi, Taiwo A., et al.
Pubblicazione: (2024)

CryptoMamba: Leveraging State Space Models for Accurate Bitcoin Price Prediction
di: Sepehri, Mohammad Shahab, et al.
Pubblicazione: (2025)

StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction
di: Wang, Shengkun, et al.
Pubblicazione: (2024)

Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling
di: Zeng, Liang, et al.
Pubblicazione: (2021)

Avocado Price Prediction Using a Hybrid Deep Learning Model: TCN-MLP-Attention Architecture
di: Zhang, Linwei, et al.
Pubblicazione: (2025)

Multistep Brent Oil Price Forecasting with a Multi-Aspect Meta-heuristic Optimization and Ensemble Deep Learning Model
di: Alruqimi, Mohammed, et al.
Pubblicazione: (2024)

Making Evidence Actionable in Adaptive Learning Closing the Diagnostic Pedagogical Loop
di: Mehrabi, Amirreza, et al.
Pubblicazione: (2025)

LendNova: Towards Automated Credit Risk Assessment with Language Models
di: Shamsi, Kiarash, et al.
Pubblicazione: (2026)

Simulation-Free Determination of Microstructure Representative Volume Element Size via Fisher Scores
di: Liu, Wei, et al.
Pubblicazione: (2024)

Intelligent Gradient Boosting Algorithms for Estimating Strength of Modified Subgrade Soil
di: Mustapha, Ismail B., et al.
Pubblicazione: (2025)

Mobile Coverage Analysis using Crowdsourced Data
di: Wong, Timothy, et al.
Pubblicazione: (2025)

Empirical Asset Pricing with Large Language Model Agents
di: Cheng, Junyan, et al.
Pubblicazione: (2024)

Unified Occupancy on a Public Transport Network through Combination of AFC and APC Data
di: Dib, Amir, et al.
Pubblicazione: (2024)

Physics-Informed Teacher-Student Ensemble Learning for Traffic State Estimation with a Varying Speed Limit Scenario
di: Huang, Archie J., et al.
Pubblicazione: (2026)

Making Evidence Actionable in Adaptive Learning
di: Mehrabi, Amirreza, et al.
Pubblicazione: (2025)

DeepSupp: Attention-Driven Correlation Pattern Analysis for Dynamic Time Series Support and Resistance Levels Identification
di: Kriuk, Boris, et al.
Pubblicazione: (2025)

Rethinking Cancer Gene Identification through Graph Anomaly Analysis
di: Zang, Yilong, et al.
Pubblicazione: (2024)

DeepFEA: Deep Learning for Prediction of Transient Finite Element Analysis Solutions
di: Triantafyllou, Georgios, et al.
Pubblicazione: (2024)

Interactive and Intelligent Root Cause Analysis in Manufacturing with Causal Bayesian Networks and Knowledge Graphs
di: Wehner, Christoph, et al.
Pubblicazione: (2024)

DK-Root: A Joint Data-and-Knowledge-Driven Framework for Root Cause Analysis of QoE Degradations in Mobile Networks
di: Li, Qizhe, et al.
Pubblicazione: (2025)

MANA-Net: Mitigating Aggregated Sentiment Homogenization with News Weighting for Enhanced Market Prediction
di: Wang, Mengyu, et al.
Pubblicazione: (2024)

CatMemo at the FinLLM Challenge Task: Fine-Tuning Large Language Models using Data Fusion in Financial Applications
di: Cao, Yupeng, et al.
Pubblicazione: (2024)

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

Financial Assets Dependency Prediction Utilizing Spatiotemporal Patterns
di: Zhu, Haoren, et al.
Pubblicazione: (2024)

Data-driven Power Flow Linearization: Theory
di: Jia, Mengshuo, et al.
Pubblicazione: (2024)

Multistep Criticality Search and Power Shaping in Microreactors with Reinforcement Learning
di: Radaideh, Majdi I., et al.
Pubblicazione: (2024)

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning
di: Chen, Shaohan, et al.
Pubblicazione: (2024)

Machine Learning-Driven Convergence Analysis in Multijurisdictional Compliance Using BERT and K-Means Clustering
di: Sonani, Raj, et al.
Pubblicazione: (2025)

Unveiling Nonlinear Dynamics in Catastrophe Bond Pricing: A Machine Learning Perspective
di: Chen, Xiaowei, et al.
Pubblicazione: (2024)

Assessing Economic Viability: A Comparative Analysis of Total Cost of Ownership for Domain-Adapted Large Language Models versus State-of-the-art Counterparts in Chip Design Coding Assistance
di: Sharma, Amit, et al.
Pubblicazione: (2024)

Modeling and Detecting Company Risks from News: A Case Study in Bloomberg News
di: Pei, Jiaxin, et al.
Pubblicazione: (2025)