Freddie Kalaitzis

628 total citations
24 papers, 228 citations indexed

About

Freddie Kalaitzis is a scholar working on Artificial Intelligence, Media Technology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Freddie Kalaitzis has authored 24 papers receiving a total of 228 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Media Technology and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Freddie Kalaitzis's work include Advanced Image Fusion Techniques (5 papers), Advanced Image Processing Techniques (4 papers) and Image and Signal Denoising Methods (3 papers). Freddie Kalaitzis is often cited by papers focused on Advanced Image Fusion Techniques (5 papers), Advanced Image Processing Techniques (4 papers) and Image and Signal Denoising Methods (3 papers). Freddie Kalaitzis collaborates with scholars based in United Kingdom, United States and Spain. Freddie Kalaitzis's co-authors include Neil D. Lawrence, Luis Gómez‐Chova, Yoshua Bengio, Yarin Gal, Samira Ebrahimi Kahou, Vincent Michalski, Gonzalo Mateo‐García, Daniel Aloise, Marie‐Ève Rancourt and Pierre-Luc St-Charles and has published in prestigious journals such as BMC Bioinformatics, The Astrophysical Journal Supplement Series and Remote Sensing.

In The Last Decade

Freddie Kalaitzis

23 papers receiving 219 citations

Peers

Freddie Kalaitzis

CVPR

GPC

Xueqing Deng China

Weijia Liu China

Matthias Heiler Germany

Qin Dai China

Antonio Mazza Italy

Zhixiang Wu China

Arkajyoti Saha India

Yibo Huang China

Eric Smith Canada

Xueqing Deng China

Freddie Kalaitzis

130 ×1.5

150 ×1.8

CVPR

44 ×1.0

45 ×1.2

21 ×0.8

GPC

Citations per year, relative to Freddie Kalaitzis Freddie Kalaitzis (= 1×) peers Xueqing Deng

Countries citing papers authored by Freddie Kalaitzis

Since Specialization

Citations

This map shows the geographic impact of Freddie Kalaitzis's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Freddie Kalaitzis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Freddie Kalaitzis more than expected).

Fields of papers citing papers by Freddie Kalaitzis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Freddie Kalaitzis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Freddie Kalaitzis. The network helps show where Freddie Kalaitzis may publish in the future.

Co-authorship network of co-authors of Freddie Kalaitzis

This figure shows the co-authorship network connecting the top 25 collaborators of Freddie Kalaitzis. A scholar is included among the top collaborators of Freddie Kalaitzis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Freddie Kalaitzis. Freddie Kalaitzis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Aybar, César, et al.. (2025). Trustworthy Super-Resolution of Multispectral Sentinel-2 Imagery With Latent Diffusion. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 6940–6952. 3 indexed citations

Aybar, César, et al.. (2024). A Comprehensive Benchmark for Optical Remote Sensing Image Super-Resolution. IEEE Geoscience and Remote Sensing Letters. 21. 1–5. 6 indexed citations

Aybar, César, et al.. (2024). SEN2NAIP: A large-scale dataset for Sentinel-2 Image Super-Resolution. Scientific Data. 11(1). 1389–1389. 6 indexed citations

Muñoz‐Jaramillo, Andrés, Paul Wright, Carl Shneider, et al.. (2024). Physically Motivated Deep Learning to Superresolve and Cross Calibrate Solar Magnetograms. The Astrophysical Journal Supplement Series. 271(2). 46–46. 3 indexed citations

Allen, Matthew R., et al.. (2024). M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and Multispectral Data. 104694–104723.

Rossi, Cristian, et al.. (2023). Entity Embeddings in Remote Sensing: Application to Deformation Monitoring for Infrastructure. Remote Sensing. 15(20). 4910–4910. 3 indexed citations

Gal, Yarin, et al.. (2023). Precipitation-Triggered Landslide Prediction in Nepal Using Machine Learning and Deep Learning. 4962–4965. 4 indexed citations

Bickel, Valentin, et al.. (2023). Superresolution of Lunar Satellite Images for Enhanced Robotic Traverse Planning: Maximizing the Value of Existing Data Products for Space Robotics. IEEE Robotics & Automation Magazine. 31(2). 100–112. 1 indexed citations

Mateo‐García, Gonzalo, et al.. (2022). Multi-spectral multi-image super-resolution of Sentinel-2 with radiometric consistency losses and its effect on building delineation. ISPRS Journal of Photogrammetry and Remote Sensing. 195. 1–13. 36 indexed citations

10.

Rancourt, Marie‐Ève, et al.. (2022). On Transfer Learning for Building Damage Assessment from Satellite Imagery in Emergency Contexts. Remote Sensing. 14(11). 2532–2532. 25 indexed citations

11.

Witt, Christian Schroeder de, Catherine Tong, Daniele De Martini, et al.. (2021). RainBench: Enabling Data-Driven Precipitation Forecasting on a Global Scale. 1 indexed citations

12.

Michalski, Vincent, Pierre-Luc St-Charles, Freddie Kalaitzis, et al.. (2020). Multi-Image Super-Resolution for Remote Sensing using Deep Recurrent Networks. 816–825. 44 indexed citations

13.

Lewenberg, Yoad, et al.. (2016). Predicting Gaming Related Properties from Twitter Accounts. Proceedings of the AAAI Conference on Artificial Intelligence. 30(1). 2 indexed citations

14.

Kalaitzis, Freddie, et al.. (2016). Predicting Gaming Related Properties from Twitter Profiles. 12. 28–35. 3 indexed citations

15.

Kalaitzis, Freddie & James D. B. Nelson. (2014). Online joint classification and anomaly detection via sparse coding. 7. 1–6. 2 indexed citations

16.

Kalaitzis, Freddie, John Lafferty, Neil D. Lawrence, & Shuheng Zhou. (2013). The Bigraphical Lasso. International Conference on Machine Learning. 28. 1229–1237. 3 indexed citations

17.

Kalaitzis, Freddie & Ricardo Silva. (2013). Flexible sampling of discrete data correlations without the marginal distributions. arXiv (Cornell University). 26. 2517–2525. 2 indexed citations

18.

Kalaitzis, Freddie & Neil D. Lawrence. (2012). Residual Components Analysis.. International Conference on Machine Learning. 6 indexed citations

19.

Kalaitzis, Freddie & Neil D. Lawrence. (2012). Residual Component Analysis: Generalising PCA for more flexible inference in linear-Gaussian models. Apollo (University of Cambridge). 29. 1 indexed citations

20.

Kalaitzis, Freddie & Neil D. Lawrence. (2011). A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression. BMC Bioinformatics. 12(1). 180–180. 58 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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