Predicting Gaming Related Properties from Twitter Accounts. - Maria Ivanova Gorinova 001; Yoad Lewenberg; Yoram Bachrach; Alfredo Kalaitzis; Michael Fagan 002; Dean Carignan; Nitin Gautam (AAAI, 2016)

Predicting Gaming Related Properties from Twitter Profiles. - Alfredo Kalaitzis; Maria Ivanova Gorinova 001; Yoad Lewenberg; Yoram Bachrach; Michael Fagan 002; Dean Carignan; Nitin Gautam (BigDataService, 2016)

A large-scale crowdsourced analysis of abuse against women journalists and politicians on Twitter. - Laure Delisle; Alfredo Kalaitzis; Krzysztof Majewski; Archy de Berker; Milena Marin; Julien Cornebise (CoRR, 2019)

Prediction of GNSS Phase Scintillations: A Machine Learning Approach. - Kara Lamb; Garima Malhotra; Athanasios Vlontzos; Edward Wagstaff; Atilim Günes Baydin; Anahita Bhiwandiwalla; Yarin Gal; Alfredo Kalaitzis; Anthony Reina; Asti Bhatt (CoRR, 2019)

Correlation of Auroral Dynamics and GNSS Scintillation with an Autoencoder. - Kara Lamb; Garima Malhotra; Athanasios Vlontzos; Edward Wagstaff; Atilim Günes Baydin; Anahita Bhiwandiwalla; Yarin Gal; Alfredo Kalaitzis; Anthony Reina; Asti Bhatt (CoRR, 2019)

Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties. - Xavier Gitiaux; Shane A. Maloney; Anna Jungbluth; Carl Shneider; Paul J. Wright; Atilim Günes Baydin; Michel Deudon; Yarin Gal; Alfredo Kalaitzis; Andrés Muñoz-Jaramillo (CoRR, 2019)

Single-Frame Super-Resolution of Solar Magnetograms: Investigating Physics-Based Metrics & Losses. - Anna Jungbluth; Xavier Gitiaux; Shane A. Maloney; Carl Shneider; Paul J. Wright; Alfredo Kalaitzis; Michel Deudon; Atilim Günes Baydin; Yarin Gal; Andrés Muñoz-Jaramillo (CoRR, 2019)

Multi-Image Super-Resolution for Remote Sensing using Deep Recurrent Networks. - Md Rifat Arefin; Vincent Michalski; Pierre-Luc St-Charles; Alfredo Kalaitzis; Sookyung Kim; Samira Ebrahimi Kahou; Yoshua Bengio (CVPR Workshops, 2020)

HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery. - Michel Deudon; Alfredo Kalaitzis; Israel Goytom; Md Rifat Arefin; Zhichao Lin; Kris Sankaran; Vincent Michalski; Samira Ebrahimi Kahou; Julien Cornebise; Yoshua Bengio (CoRR, 2020)

Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery. - Issam H. Laradji; Pau Rodríguez; Freddie Kalaitzis; David Vázquez 001; Ross Young; Ed Davey; Alexandre Lacoste (CoRR, 2020)

Pix2Streams: Dynamic Hydrology Maps from Satellite-LiDAR Fusion. - Dolores Garcia; Gonzalo Mateo-Garcia; Hannes Bernhardt; Ron Hagensieker; Ignacio G. Lopez Francos; Jonathan Stock; Guy Schumann; Kevin Dobbs; Freddie Kalaitzis (CoRR, 2020)

RainBench: Towards Global Precipitation Forecasting from Satellite Imagery. - Christian Schröder de Witt; Catherine Tong; Valentina Zantedeschi; Daniele De Martini; Freddie Kalaitzis; Matthew Chantry; Duncan Watson-Parris; Piotr Bilinski (CoRR, 2020)

Converter software to calibrate and super-resolve solar magnetograms. - Andrés Muñoz-Jaramillo; Xavier Gitiaux; Anna Jungbluth; Shane A. Maloney; Carl Shneider; Paul J. Wright; Michel Deudon; Alfredo Kalaitzis; Atilim Günes Baydin; Yarin Gal (Zenodo, 2020)

RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery. - Christian Schröder de Witt; Catherine Tong; Valentina Zantedeschi; Daniele De Martini; Alfredo Kalaitzis; Matthew Chantry; Duncan Watson-Parris; Piotr Bilinski (AAAI, 2021)

Multi-Spectral Multi-Image Super-Resolution of Sentinel-2 with Radiometric Consistency Losses and Its Effect on Building Delineation. - Muhammed Razzak; Gonzalo Mateo-Garcia; Luis Gómez-Chova; Yarin Gal; Freddie Kalaitzis (CoRR, 2021)

Open High-Resolution Satellite Imagery: The WorldStrat Dataset - With Application to Super-Resolution. - Julien Cornebise; Ivan Orsolic; Freddie Kalaitzis (NeurIPS, 2022)

Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes. - Vanessa Böhm; Wei Ji Leong; Ragini Bal Mahesh; Ioannis Prapas; Edoardo Nemni; Freddie Kalaitzis; Siddha Ganju; Raúl Ramos-Pollán (CoRR, 2022)

SAR-based landslide classification pretraining leads to better segmentation. - Vanessa Böhm; Wei Ji Leong; Ragini Bal Mahesh; Ioannis Prapas; Edoardo Nemni; Freddie Kalaitzis; Siddha Ganju; Raúl Ramos-Pollán (CoRR, 2022)

Deep learning based landslide density estimation on SAR data for rapid response. - Vanessa Boehm; Wei Ji Leong; Ragini Bal Mahesh; Ioannis Prapas; Edoardo Nemni; Freddie Kalaitzis; Siddha Ganju; Raúl Ramos-Pollán (CoRR, 2022)

On Transfer Learning for Building Damage Assessment from Satellite Imagery in Emergency Contexts. - Isabelle Bouchard; Marie-Ève Rancourt; Daniel Aloise; Freddie Kalaitzis (Remote. Sens., 2022)

Entity Embeddings in Deep Learning for the Detection of Anomalous Insar Deformation Signals. - Maral Bayaraa; Cristian Rossi; Alfredo Kalaitzis; Brian Sheil (IGARSS, 2023)

Precipitation-Triggered Landslide Prediction in Nepal Using Machine Learning and Deep Learning. - Kelsey Doerksen; Yarin Gal; Freddie Kalaitzis; Cristian Rossi; David Petit; Sihan Li; Simon J. Dadson (IGARSS, 2023)

A Contrastive Method Based on Elevation Data for Remote Sensing with Scarce and High Level Semantic Labels. - Omar A. Castaño-Idarraga; Raúl Ramos-Pollán; Freddie Kalaitzis (CoRR, 2023)

Fewshot learning on global multimodal embeddings for earth observation tasks. - Matt Allen 001; Francisco Dorr; Joseph A. Gallego-Mejia; Laura Martínez-Ferrer; Anna Jungbluth; Freddie Kalaitzis; Raúl Ramos-Pollán (CoRR, 2023)

Large Scale Masked Autoencoding for Reducing Label Requirements on SAR Data. - Matt Allen 001; Francisco Dorr; Joseph A. Gallego-Mejia; Laura Martínez-Ferrer; Anna Jungbluth; Freddie Kalaitzis; Raúl Ramos-Pollán (CoRR, 2023)

Exploring Generalisability of Self-Distillation with No Labels for SAR-Based Vegetation Prediction. - Laura Martínez-Ferrer; Anna Jungbluth; Joseph A. Gallego-Mejia; Matt Allen 001; Francisco Dorr; Freddie Kalaitzis; Raúl Ramos-Pollán (CoRR, 2023)

Exploring DINO: Emergent Properties and Limitations for Synthetic Aperture Radar Imagery. - Joseph A. Gallego-Mejia; Anna Jungbluth; Laura Martínez-Ferrer; Matt Allen 001; Francisco Dorr; Freddie Kalaitzis; Raúl Ramos-Pollán (CoRR, 2023)

Entity Embeddings in Remote Sensing: Application to Deformation Monitoring for Infrastructure. - Maral Bayaraa; Cristian Rossi; Freddie Kalaitzis; Brian Sheil (Remote. Sens., 2023)

M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and Multispectral Data. - Matthew J. Allen 001; Francisco Dorr; Joseph Alejandro Gallego-Mejia; Laura Martínez-Ferrer; Anna Jungbluth; Freddie Kalaitzis; Raúl Ramos-Pollán (NeurIPS, 2024)

M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and RGB Data. - Matthew J. Allen 001; Francisco Dorr; Joseph Alejandro Gallego-Mejia; Laura Martínez-Ferrer; Anna Jungbluth; Freddie Kalaitzis; Raúl Ramos-Pollán (CoRR, 2024)

Uncertainty and Generalizability in Foundation Models for Earth Observation. - Raúl Ramos-Pollán; Freddie Kalaitzis; Karthick Panner Selvam (CoRR, 2024)

Rapid Adaptation of Earth Observation Foundation Models for Segmentation. - Karthick Panner Selvam; Raúl Ramos-Pollán; Freddie Kalaitzis (CoRR, 2024)

A Comprehensive Benchmark for Optical Remote Sensing Image Super-Resolution. - César Aybar; David Montero 001; Simon Donike; Freddie Kalaitzis; Luis Gómez-Chova (IEEE Geosci. Remote. Sens. Lett., 2024)

Superresolution of Lunar Satellite Images for Enhanced Robotic Traverse Planning: Maximizing the Value of Existing Data Products for Space Robotics. - Jose Ignacio Delgado-Centeno; Paula Harder; Valentin Tertius Bickel; Ben Moseley; Freddie Kalaitzis; Siddha Ganju; Miguel A. Olivares-Méndez (IEEE Robotics Autom. Mag., 2024)

Trustworthy Super-Resolution of Multispectral Sentinel-2 Imagery With Latent Diffusion. - Simon Donike; César Aybar; Luis Gómez-Chova; Freddie Kalaitzis (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)

Dargana: fine-tuning EarthPT for dynamic tree canopy mapping from space. - Michael J. Smith 013; Luke Fleming; James E. Geach; Ryan J. Roberts; Freddie Kalaitzis; James Banister (CoRR, 2025)

Uncertainty Quantification for Surface Ozone Emulators using Deep Learning. - Kelsey Doerksen; Yuliya Marchetti; Steven Lu; Kevin Bowman; James Montgomery; Kazuyuki Miyazaki; Yarin Gal; Freddie Kalaitzis (CoRR, 2025)

Leveraging Deep Learning for Physical Model Bias of Global Air Quality Estimates. - Kelsey Doerksen; Yuliya Marchetti; Kevin Bowman; Steven Lu; James Montgomery; Yarin Gal; Freddie Kalaitzis; Kazuyuki Miyazaki (CoRR, 2025)