Publications of Rafal A. Angryk

A list of publications authored or co-authored by Rafal A. Angryk, derived from the SAO/NASA Astrophysics Data System (ADS). The number in brackets after each title indicates the number of citations that the paper has received.

Orcid ID: 0000-0001-9598-8207

List of publications ordered by citations
Number of papers: 35 (refereed: 21)
No. of citations: 308
First author papers: 1 (refereed: 1)

2025

  1. Outlier Detection and Removal in Multivariate Time Series for a More Robust Machine Learning─based Solar Flare Prediction [0]
    Wen, Junzhi, Ahmadzadeh, Azim, Georgoulis, Manolis K., Sadykov, Viacheslav M. & Angryk, Rafal A., ApJS, 277, 60

2023

  1. A Systematic Magnetic Polarity Inversion Line Data Set from SDO/HMI Magnetograms [11]
    Ji, Anli, Cai, Xumin, Khasayeva, Nigar, Georgoulis, Manolis K., Martens, Petrus C., Angryk, Rafal A. & Aydin, Berkay, ApJS, 265, 28
  2. Explaining Full-Disk Deep Learning Model for Solar Flare Prediction Using Attribution Methods [8]
    Pandey, Chetraj, Angryk, Rafal A. & Aydin, Berkay, Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track. ECML PKDD 2023. Lecture Notes in Computer Science, 14175, p. 72
  3. Explainable Deep Learning-Based Solar Flare Prediction with Post Hoc Attention for Operational Forecasting [5]
    Pandey, Chetraj, Angryk, Rafal A., Georgoulis, Manolis K. & Aydin, Berkay, Lecture Notes in Computer Science, 14276, 567

2021

  1. Avoiding More Accurate and Less Robust Models: Mistakes and Pitfalls in Training Flare Forecasting Models [0]
    Ahmadzadeh, Azim, Aydin, Berkay, Kempton, Dustin, Mahajan, Sushant, Georgoulis, Manolis & Angryk, Rafal, essoar.10508359
  2. How to Train Your Flare Prediction Model: Revisiting Robust Sampling of Rare Events [63]
    Ahmadzadeh, Azim, Aydin, Berkay, Georgoulis, Manolis K., Kempton, Dustin J., Mahajan, Sushant S. & Angryk, Rafal A., ApJS, 254, 23
  3. An ML-Ready Filament Augmentation Engine with Labeled Magnetic Helicity Sign [0]
    Talla, Shreejaa, Ahmadzadeh, Azim, Mahajan, Sushant & Angryk, Rafal, essoar.10509388
  4. Twenty Feature Selection Algorithms, One Dataset, One Problem: Flare Forecasting [0]
    Yeolekar, Atharv, Patel, Sagar, Tall, Shreejaa, Rukmini Puthucode, Krishna, Ahmadzadeh, Azim, Sadykov, Viacheslav & Angryk, Rafal, essoar.10509390

2019

  1. A Curated Image Parameter Data Set from the Solar Dynamics Observatory Mission [8]
    Ahmadzadeh, Azim, Kempton, Dustin J. & Angryk, Rafal A., ApJS, 243, 18

2018

  1. Prediction of Solar Eruptions Using Filament Metadata [21]
    Aggarwal, Ashna, Schanche, Nicole, Reeves, Katharine K., Kempton, Dustin & Angryk, Rafal, ApJS, 236, 15
  2. Spatiotemporal Interpolation Methods for Solar Event Trajectories [5]
    Filali Boubrahimi, Soukaina, Aydin, Berkay, Schuh, Michael A., Kempton, Dustin, Angryk, Rafal A. & Ma, Ruizhe, ApJS, 236, 23
  3. Tracking Solar Phenomena from the SDO [4]
    Kempton, Dustin J., Schuh, Michael A. & Angryk, Rafal A., ApJ, 869, 54
  4. Coronal Mass Ejection Data Clustering and Visualization of Decision Trees [7]
    Ma, Ruizhe, Angryk, Rafal A., Riley, Pete & Filali Boubrahimi, Soukaina, ApJS, 236, 14
  5. Data Handling and Assimilation for Solar Event Prediction [9]
    Martens, Petrus C. & Angryk, Rafal A., Space Weather of the Heliosphere: Processes and Forecasts (Editors: Foullon, Claire & Malandraki, Olga E.), IAU Symposium, 335, p. 344

2017

  1. Measuring the Significance of Spatiotemporal Co-Occurrences [0]
    Aydin, Berkay, Kucuk, Ahmet, Angryk, Rafal A. & Martens, Petrus C., ACM Transactions on Spatial Algorithms and Systems, 3, 1
  2. A large-scale solar dynamics observatory image dataset for computer vision applications [11]
    Kucuk, Ahmet, Banda, Juan M. & Angryk, Rafal A., Scientific Data, 4, 170096

2016

  1. Discovering spatiotemporal event sequences [1]
    Aydin, Berkay & Angryk, Rafal, Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, p. 46
  2. Mining spatiotemporal co-occurrence patterns in non-relational databases [5]
    Aydin, Berkay, Akkineni, Vijay & Angryk, Rafal, GeoInformatica, 20, 801
  3. SOLEV: a video generation framework for solar events from mixed data sources (demo paper) [0]
    Boubrahimi, Soukaina Filali, Aydin, Berkay, Kempton, Dustin & Angryk, Rafal A., Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, p. 1
  4. Mining At Most Top-K% Spatiotemporal Co-occurrence Patterns in Datasets with Extended Spatial Representations [0]
    Pillai, Karthik Ganesan, Angryk, Rafal A., Banda, Juan M., Kempton, Dustin, Aydin, Berkay & Martens, Petrus C., ACM Transactions on Spatial Algorithms and Systems, 2, 1
  5. A large-scale dataset of solar event reports from automated feature recognition modules [5]
    Schuh, Michael A., Angryk, Rafal A. & Martens, Petrus C., Journal of Space Weather and Space Climate, 6, A22

2015

  1. Special Section: Management, Search and Analysis of Solar Astronomy Big Data [0]
    Angryk, Rafal A., Csillaghy, André & Martens, Petrus C., Astronomy and Computing, 13, 85
  2. Mining spatiotemporal co-occurrence patterns in solar datasets [5]
    Aydin, B., Kempton, D., Akkineni, V., Angryk, R. & Pillai, K. G., Astronomy and Computing, 13, 136
  3. Time-efficient significance measure for discovering spatiotemporal co-occurrences from data with unbalanced characteristics [1]
    Aydin, Berkay, Akkineni, Vijay & Angryk, Rafal, Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, p. 1
  4. Regional content-based image retrieval for solar images: Traditional versus modern methods [1]
    Banda, J. M. & Angryk, R. A., Astronomy and Computing, 13, 108
  5. Tracking Solar Events through Iterative Refinement [9]
    Kempton, D. J. & Angryk, R. A., Astronomy and Computing, 13, 124
  6. Solar image parameter data from the SDO: Long-term curation and data mining [4]
    Schuh, M. A., Angryk, R. A. & Martens, P. C., Astronomy and Computing, 13, 86
  7. On visualization techniques for solar data mining [5]
    Schuh, M. A., Banda, J. M., Wylie, T., McInerney, P., Pillai, K. Ganesan & Angryk, R. A., Astronomy and Computing, 10, 32

2014

  1. A Comparative Evaluation of Automated Solar Filament Detection [13]
    Schuh, M. A., Banda, J. M., Bernasconi, P. N., Angryk, R. A. & Martens, P. C. H., Solar Physics, 289, 2503

2013

  1. Steps Toward a Large-Scale Solar Image Data Analysis to Differentiate Solar Phenomena [6]
    Banda, J. M., Angryk, R. A. & Martens, P. C. H., Solar Physics, 288, 435
  2. On Dimensionality Reduction for Indexing and Retrieval of Large-Scale Solar Image Data [4]
    Banda, J. M., Angryk, R. A. & Martens, P. C. H., Solar Physics, 283, 113
  3. A filter-and-refine approach to mine spatiotemporal co-occurrences [3]
    Pillai, Karthik Ganesan, Angryk, Rafal A. & Aydin, Berkay, Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, p. 104
  4. An IEEE Standards-Based Visualization Tool for Knowledge Discovery in Maintenance Event Sequences [0]
    Schuh, Michael, Sheppard, John, Strasser, Shane, Angryk, Rafal & Izurieta, Clemente, IEEE Aerospace and Electronic Systems Magazine, 28, 30

2012

  1. Computer Vision for the Solar Dynamics Observatory (SDO) [94]
    Martens, P. C. H., Attrill, G. D. R., Davey, A. R., Engell, A., Farid, S., Grigis, P. C., Kasper, J., Korreck, K., Saar, S. H., Savcheva, A., Su, Y., Testa, P., Wills-Davey, M., Bernasconi, P. N., Raouafi, N.-E., Delouille, V. A., Hochedez, J. F., Cirtain, J. W., DeForest, C. E., Angryk, R. A., De Moortel, I., Wiegelmann, T., Georgoulis, M. K., McAteer, R. T. J. & Timmons, R. P., Solar Physics, 275, 79

2009

  1. An Abstraction-Based Data Model for Information Retrieval [0]
    McAllister, Richard A. & Angryk, Rafal A., Lecture Notes in Computer Science, p.567

Created on Thu Feb 12 17:39:53 2026.