:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Serafin, Tomasz, Nitka, Weronika
Format:	Preprint
Published:	2025
Subjects:	Applications Machine Learning
Online Access:	https://arxiv.org/abs/2510.15011
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Forecasting Electricity Prices
by: Maciejowska, Katarzyna, et al.
Published: (2022)

AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting
by: Das, Keshav, et al.
Published: (2025)

Probabilistic intraday electricity price forecasting using generative machine learning
by: Chen, Jieyu, et al.
Published: (2025)

Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting
by: Hirsch, Simon
Published: (2025)

Bayesian Hierarchical Probabilistic Forecasting of Intraday Electricity Prices
by: Nickelsen, Daniel, et al.
Published: (2024)

Transfer Learning using 66 Diseases for Disease Forecasting Applications
by: Beesley, Lauren J, et al.
Published: (2026)

Monitoring Machine Learning Forecasts for Platform Data Streams
by: Rombouts, Jeroen, et al.
Published: (2024)

Spatio-temporal DeepKriging in PyTorch: A Supplementary Application to Precipitation Data for Interpolation and Probabilistic Forecasting
by: Nag, Pratik
Published: (2025)

Regime-Aware Conditional Neural Processes with Multi-Criteria Decision Support for Operational Electricity Price Forecasting
by: Das, Abhinav, et al.
Published: (2025)

Informed Forecasting: Leveraging Auxiliary Knowledge to Boost LLM Performance on Time Series Forecasting
by: Ghasemloo, Mohammadmahdi, et al.
Published: (2025)

Federated Learning for Financial Forecasting
by: Noseda, Manuel, et al.
Published: (2025)

MMformer with Adaptive Transferable Attention: Advancing Multivariate Time Series Forecasting for Environmental Applications
by: Xin, Ning, et al.
Published: (2025)

Neural Networks for Extreme Quantile Regression with an Application to Forecasting of Flood Risk
by: Pasche, Olivier C., et al.
Published: (2022)

Simplifying Random Forests' Probabilistic Forecasts
by: Koster, Nils, et al.
Published: (2024)

Improving Geopolitical Forecasts with Bayesian Networks
by: Martin, Matthew
Published: (2026)

Generative Probabilistic Time Series Forecasting and Applications in Grid Operations
by: Wang, Xinyi, et al.
Published: (2024)

Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices
by: Berrisch, Jonathan, et al.
Published: (2023)

Probabilistic Forecasts of Load, Solar and Wind for Electricity Price Forecasting
by: Uniejewski, Bartosz, et al.
Published: (2025)

Dynamic Attention (DynAttn): Interpretable High-Dimensional Spatio-Temporal Forecasting (with Application to Conflict Fatalities)
by: Iacus, Stefano M., et al.
Published: (2025)

Weather-Related Crash Risk Forecasting: A Deep Learning Approach for Heterogenous Spatiotemporal Data
by: Ogungbire, Abimbola, et al.
Published: (2026)

Sparse Variational Contaminated Noise Gaussian Process Regression with Applications in Geomagnetic Perturbations Forecasting
by: Iong, Daniel, et al.
Published: (2024)

DeepMIDE: A Multi-Output Spatio-Temporal Method for Ultra-Scale Offshore Wind Energy Forecasting
by: Ye, Feng, et al.
Published: (2024)

Predictive Uncertainty in Short-Term PV Forecasting under Missing Data: A Multiple Imputation Approach
by: Pashmchi, Parastoo, et al.
Published: (2026)

Adaptive Multi-task Learning for Probabilistic Load Forecasting
by: Zaballa, Onintze, et al.
Published: (2025)

Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting
by: S, Saranya Ganesh, et al.
Published: (2025)

Forecasting West Nile virus with deep graph encoders
by: Greiffenstein, Ethan, et al.
Published: (2025)

Transportation Marketplace Rate Forecast Using Signature Transform
by: Gu, Haotian, et al.
Published: (2024)

BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network
by: Liu, Yongzheng, et al.
Published: (2025)

Forecast reconciliation with non-linear constraints
by: Girolimetto, Daniele, et al.
Published: (2025)

Evaluating Weather Forecasts from a Decision Maker's Perspective
by: Raeth, Kornelius, et al.
Published: (2025)

Forecasting the future development in quality and value of professional football players
by: van Arem, Koen W., et al.
Published: (2025)

The Living Forecast: Evolving Day-Ahead Predictions into Intraday Reality
by: Bölat, Kutay, et al.
Published: (2025)

Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble Forecasts
by: Pic, Romain, et al.
Published: (2024)

Copula Conformal Prediction for Multi-step Time Series Forecasting
by: Sun, Sophia, et al.
Published: (2022)

Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects
by: Wang, Hao, et al.
Published: (2026)

Calibrated Predictive Lower Bounds on Time-to-Unsafe-Sampling in LLMs
by: Davidov, Hen, et al.
Published: (2025)

Application of Machine Learning in Stock Market Forecasting: A Case Study of Disney Stock
by: Huang, Dengxin
Published: (2023)

Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction
by: Moradi, Alireza, et al.
Published: (2025)

CLVAE: A Variational Autoencoder for Long-Term Customer Revenue Forecasting
by: Näf, Jeffrey, et al.
Published: (2026)

Forecasting West Nile Virus with Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data
by: Tonks, Adam, et al.
Published: (2022)