Saved in:
| Main Author: | Nan, Zhaojin |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.06654 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Estimating causal effects of customer satisfaction on downstream metrics in a multi-queue contact center
by: Orellana, Sebastián, et al.
Published: (2024)
by: Orellana, Sebastián, et al.
Published: (2024)
A scalable Bayesian double machine learning framework for high dimensional causal estimation, with application to racial disproportionality assessment
by: Luo, Yu, et al.
Published: (2025)
by: Luo, Yu, et al.
Published: (2025)
A machine learning approach to study plant functional trait divergence
by: Sambadi Majumder, et al.
Published: (2024)
by: Sambadi Majumder, et al.
Published: (2024)
Bunting and the ghost runner: a causal inference approach
by: Cummiskey, Kevin, et al.
Published: (2024)
by: Cummiskey, Kevin, et al.
Published: (2024)
A network and machine learning approach to detect Value Added Tax fraud
by: Alexopoulos, Angelos, et al.
Published: (2021)
by: Alexopoulos, Angelos, et al.
Published: (2021)
A machine learning approach based on survival analysis for IBNR frequencies in non-life reserving
by: Hiabu, Munir, et al.
Published: (2023)
by: Hiabu, Munir, et al.
Published: (2023)
Beyond Beats: A Recipe to Song Popularity? A machine learning approach
by: Sebastian, Niklas, et al.
Published: (2024)
by: Sebastian, Niklas, et al.
Published: (2024)
Forecasting solar power output in Ibadan: A machine learning approach leveraging weather data and system specifications
by: Urhuerhi, Obarotu Peter, et al.
Published: (2025)
by: Urhuerhi, Obarotu Peter, et al.
Published: (2025)
Predicting loss-of-function impact of genetic mutations: a machine learning approach
by: Kaur, Arshmeet, et al.
Published: (2024)
by: Kaur, Arshmeet, et al.
Published: (2024)
A two-step machine learning approach to statistical post-processing of weather forecasts for power generation
by: Baran, Ágnes, et al.
Published: (2022)
by: Baran, Ágnes, et al.
Published: (2022)
Validity in machine learning for extreme event attribution
by: Chou, Cassandra C., et al.
Published: (2025)
by: Chou, Cassandra C., et al.
Published: (2025)
Traffic noise assessment in urban Bulgaria using explainable machine learning
by: Helbic, Marco, et al.
Published: (2025)
by: Helbic, Marco, et al.
Published: (2025)
The contribution of machine learning to the prevention of burnout among healthcare workers in Morocco
by: Eddaou, Mohammed
Published: (2025)
by: Eddaou, Mohammed
Published: (2025)
Do we actually understand the impact of renewables on electricity prices? A causal inference approach
by: Cacciarelli, Davide, et al.
Published: (2025)
by: Cacciarelli, Davide, et al.
Published: (2025)
Robust Bayesian causal estimation for causal inference in medical diagnosis
by: Basu, Tathagata, et al.
Published: (2024)
by: Basu, Tathagata, et al.
Published: (2024)
A representation-learning approach for insurance pricing with images
by: Blier-Wong, Christopher, et al.
Published: (2023)
by: Blier-Wong, Christopher, et al.
Published: (2023)
Causal machine learning for predicting treatment outcomes
by: Feuerriegel, Stefan, et al.
Published: (2024)
by: Feuerriegel, Stefan, et al.
Published: (2024)
A machine learning approach to predict university enrolment choices through students' high school background in Italy
by: Priulla, Andrea, et al.
Published: (2024)
by: Priulla, Andrea, et al.
Published: (2024)
Double machine learning to estimate the effects of multiple treatments and their interactions
by: Xiang, Qingyan, et al.
Published: (2025)
by: Xiang, Qingyan, et al.
Published: (2025)
Assessing variable importance in survival analysis using machine learning
by: Wolock, Charles J., et al.
Published: (2023)
by: Wolock, Charles J., et al.
Published: (2023)
Surface temperature extremes produced by huge machine learning hindcasts of summer 2023
by: Risser, Mark, et al.
Published: (2026)
by: Risser, Mark, et al.
Published: (2026)
Are machine learning interpretations reliable? A stability study on global interpretations
by: Gan, Luqin, et al.
Published: (2025)
by: Gan, Luqin, et al.
Published: (2025)
A random forest machine learning model to detect fluvial hazards
by: Marco Gava, et al.
Published: (2024)
by: Marco Gava, et al.
Published: (2024)
Identification of socioeconomic factors influencing global food price security using machine learning
by: Shan, Shan
Published: (2024)
by: Shan, Shan
Published: (2024)
Probabilistic storyline attribution using machine learning
by: Loer, Frieder, et al.
Published: (2026)
by: Loer, Frieder, et al.
Published: (2026)
Rank-based transfer learning for high-dimensional survival data with application to sepsis data
by: Qiao, Nan, et al.
Published: (2025)
by: Qiao, Nan, et al.
Published: (2025)
Waiting for Dabo: A machine learning model for predicting Power 4 college football coaching hire success
by: Schuckers, Michael, et al.
Published: (2025)
by: Schuckers, Michael, et al.
Published: (2025)
Do machine learning methods lead to similar individualized treatment rules? A comparison study on real data
by: Bouvier, Florie, et al.
Published: (2023)
by: Bouvier, Florie, et al.
Published: (2023)
A comprehensive study on causal discovery between degradation paths
by: Chen, Shi-Shun, et al.
Published: (2026)
by: Chen, Shi-Shun, et al.
Published: (2026)
Analysis of points outcome in ATP Grand Slam Tennis using big data and machine learning
by: Illum, Martin, et al.
Published: (2025)
by: Illum, Martin, et al.
Published: (2025)
Assessing the influence of social media feedback on traveler's future trip-planning behavior: A multi-model machine learning approach
by: Mukherjee, Sayantan, et al.
Published: (2025)
by: Mukherjee, Sayantan, et al.
Published: (2025)
Applications of machine learning to predict seasonal precipitation for East Africa
by: Scheuerer, Michael, et al.
Published: (2024)
by: Scheuerer, Michael, et al.
Published: (2024)
Granger causal inference for climate change attribution
by: Risser, Mark D., et al.
Published: (2024)
by: Risser, Mark D., et al.
Published: (2024)
A Bayesian semi-parametric approach to causal mediation for longitudinal mediators and time-to-event outcomes with application to a cardiovascular disease cohort study
by: Bhandari, Saurabh, et al.
Published: (2024)
by: Bhandari, Saurabh, et al.
Published: (2024)
Stochastic modeling of particle structures in spray fluidized bed agglomeration using methods from machine learning
by: Fuchs, Lukas, et al.
Published: (2025)
by: Fuchs, Lukas, et al.
Published: (2025)
Certification of MPC-based zonal controller security properties using accuracy-aware machine learning proxies
by: Houdouin, Pierre, et al.
Published: (2024)
by: Houdouin, Pierre, et al.
Published: (2024)
Using spatial extreme-value theory with machine learning to model and understand spatially compounding weather extremes
by: Koh, Jonathan, et al.
Published: (2024)
by: Koh, Jonathan, et al.
Published: (2024)
Match predictions in soccer: Machine learning vs. Poisson approaches
by: Fischer, Mirko, et al.
Published: (2024)
by: Fischer, Mirko, et al.
Published: (2024)
A machine learning algorithm for the automatic classification of Phytophthora infestans genotypes into clonal lineages
by: Camilo Patarroyo, et al.
Published: (2024)
by: Camilo Patarroyo, et al.
Published: (2024)
Probabilistic intraday electricity price forecasting using generative machine learning
by: Chen, Jieyu, et al.
Published: (2025)
by: Chen, Jieyu, et al.
Published: (2025)
Similar Items
-
Estimating causal effects of customer satisfaction on downstream metrics in a multi-queue contact center
by: Orellana, Sebastián, et al.
Published: (2024) -
A scalable Bayesian double machine learning framework for high dimensional causal estimation, with application to racial disproportionality assessment
by: Luo, Yu, et al.
Published: (2025) -
A machine learning approach to study plant functional trait divergence
by: Sambadi Majumder, et al.
Published: (2024) -
Bunting and the ghost runner: a causal inference approach
by: Cummiskey, Kevin, et al.
Published: (2024) -
A network and machine learning approach to detect Value Added Tax fraud
by: Alexopoulos, Angelos, et al.
Published: (2021)