Cover Image

Data is missing again -- Reconstruction of power generation data using $k$-Nearest Neighbors and spectral graph theory

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pierrot, Amandine, Pinson, Pierre
Format:	Preprint
Published:	2024
Subjects:	Applications Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Do we actually understand the impact of renewables on electricity prices? A causal inference approach
by: Cacciarelli, Davide, et al.
Published: (2025)

Reservoir Static Property Estimation Using Nearest-Neighbor Neural Network
by: Wang, Yuhe
Published: (2024)

Likelihood-Free Estimation for Spatiotemporal Hawkes processes with missing data and application to predictive policing
by: Das, Pramit, et al.
Published: (2025)

A two-step machine learning approach to statistical post-processing of weather forecasts for power generation
by: Baran, Ágnes, et al.
Published: (2022)

A review of feature selection strategies utilizing graph data structures and knowledge graphs
by: Shao, Sisi, et al.
Published: (2024)

(Weighted) Adaptive Radius Near Neighbor Search: Evaluation for WiFi Fingerprint-based Positioning
by: Le, Khang, et al.
Published: (2026)

SPINEX: Similarity-based Predictions and Explainable Neighbors Exploration for Regression and Classification Tasks in Machine Learning
by: Naser, M. Z., et al.
Published: (2023)

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

Multimodality Stacking with Blockwise missing values and application to the PIONeeR biomarkers study for prediction of resistance to immunotherapy
by: Boussena, Mohamed, et al.
Published: (2026)

Prediction-powered Inference by Mixture of Experts
by: Gu, Yanwu, et al.
Published: (2026)

Anomaly detection using data depth: multivariate case
by: Mozharovskyi, Pavlo, et al.
Published: (2022)

Probabilistic Spatial Interpolation of Sparse Data using Diffusion Models
by: Tsao, Valerie, et al.
Published: (2025)

Pandemic model with data-driven phase detection, a study using COVID-19 data
by: Liu, Yuansan, et al.
Published: (2021)

The temporal overfitting problem with applications in wind power curve modeling
by: Prakash, Abhinav, et al.
Published: (2020)

Fusing Climate Data Products using a Spatially Varying Autoencoder
by: Johnson, Jacob A., et al.
Published: (2024)

Leveraging generative adversarial networks with spatially adaptive denormalization for multivariate stochastic seismic data inversion
by: Miele, Roberto, et al.
Published: (2025)

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

Machine Learning-based Layer-wise Detection of Overheating Anomaly in LPBF using Photodiode Data
by: Hasan, Nazmul, et al.
Published: (2024)

Challenges for Predictive Modeling with Neural Network Techniques using Error-Prone Dietary Intake Data
by: Spicker, Dylan, et al.
Published: (2023)

Predicting VBAC Outcomes from U.S. Natality Data using Deep and Classical Machine Learning Models
by: Anand, Ananya
Published: (2025)

Common Structure Discovery in Collections of Bipartite Networks: Application to Pollination Systems
by: Lacoste, Louis, et al.
Published: (2025)

Manifold Dimension Estimation via Local Graph Structure
by: Bi, Zelong, et al.
Published: (2025)

A Survey and Comparative Evaluation of Intrinsic Dimension Estimators under the Manifold Hypothesis
by: Bi, Zelong, et al.
Published: (2025)

Toward using explainable data-driven surrogate models for treating performance-based seismic design as an inverse engineering problem
by: Esteghamati, Mohsen Zaker
Published: (2025)

Automobile demand forecasting: Spatiotemporal and hierarchical modeling, life cycle dynamics, and user-generated online information
by: Nahrendorf, Tom, et al.
Published: (2025)

Change-point Detection and Segmentation of Discrete Data using Bayesian Context Trees
by: Lungu, Valentinian, et al.
Published: (2022)

Joint Models for Handling Non-Ignorable Missing Data using Bayesian Additive Regression Trees: Application to Leaf Photosynthetic Traits Data
by: Goh, Yong Chen, et al.
Published: (2024)

Missing data imputation for noisy time-series data and applications in healthcare
by: Le, Lien P., et al.
Published: (2024)

AI-based Mapping of the Conservation Status of Orchid Assemblages at Global Scale
by: Estopinan, Joaquim, et al.
Published: (2024)

Pooling Probabilistic Forecasts for Cooperative Wind Power Offering
by: Wen, Honglin, et al.
Published: (2025)

Efficient Synthetic Network Generation via Latent Embedding Reconstruction
by: Jiang, Feifan, et al.
Published: (2026)

Clusterability test for categorical data
by: Hu, Lianyu, et al.
Published: (2023)

Methods for generating and evaluating synthetic longitudinal patient data: a systematic review
by: Perkonoja, Katariina, et al.
Published: (2023)

Efficient Prediction of Pass@k Scaling in Large Language Models
by: Kazdan, Joshua, et al.
Published: (2025)

Multinomial belief networks for healthcare data
by: Donker, H. C., et al.
Published: (2023)

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

Context-Aware Automated Passenger Counting Data Denoising
by: Cherrier, Noëlie, et al.
Published: (2024)

Multi-task Modeling for Engineering Applications with Sparse Data
by: Comlek, Yigitcan, et al.
Published: (2026)

Graph Data Modeling: Molecules, Proteins, & Chemical Processes
by: Barraza-Chavez, José Manuel, et al.
Published: (2025)

Starting Off on the Wrong Foot: Pitfalls in Data Preparation
by: Guo, Jiayi, et al.
Published: (2026)