The effect of class imbalance on case selection for case-based classifiers, with emphasis on computer-aided diagnosis systems. - Jordan M. Malof; Maciej A. Mazurowski; Georgia D. Tourassi (IJCNN, 2009)

A comparative study of database reduction methods for case-based computer-aided detection systems: preliminary results. - Maciej A. Mazurowski; Jordan M. Malof; Jacek M. Zurada; Georgia D. Tourassi (Computer-Aided Diagnosis, 2009)

Optimizing drug therapy with Reinforcement Learning: The case of Anemia Management. - Jordan M. Malof; Adam E. Gaweda (IJCNN, 2011)

The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support. - Jordan M. Malof; Maciej A. Mazurowski; Georgia D. Tourassi (Neural Networks, 2012)

Statistical Models for Improving the Rate of Advance of Buried Target Detection Systems. - Jordan M. Malof (2015)

Leveraging seed dictionaries to improve dictionary learning. - Daniël Reichman 002; Jordan M. Malof; Leslie M. Collins (ICIP, 2016)

Automatic Detection of Solar Photovoltaic Arrays in High Resolution Aerial Imagery. - Jordan M. Malof; Kyle Bradbury; Leslie M. Collins; Richard G. Newell (CoRR, 2016)

A Probabilistic Model for Designing Multimodality Landmine Detection Systems to Improve Rates of Advance. - Jordan M. Malof; Kenneth D. Morton; Leslie M. Collins; Peter A. Torrione (IEEE Trans. Geosci. Remote. Sens., 2016)

Trading spatial resolution for improved accuracy in remote sensing imagery: an empirical study using synthetic data. - Jordan M. Malof; Sravya Chelikani; Leslie M. Collins; Kyle Bradbury (AIPR, 2017)

The poor generalization of deep convolutional networks to aerial imagery from new geographic locations: an empirical study with solar array detection. - Rui Wang; Joseph A. Camilo; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (AIPR, 2017)

A deep convolutional neural network, with pre-training, for solar photovoltaic array detection in aerial imagery. - Jordan M. Malof; Leslie M. Collins; Kyle Bradbury (IGARSS, 2017)

Trading spatial resolution for improved accuracy when using detection algorithms on remote sensing imagery. - Shengxin Qian; Sravya Chelikani; Patrick Wang 003; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (IGARSS, 2017)

Estimating the electricity generation capacity of solar photovoltaic arrays using only color aerial imagery. - Brenda So; Cory Nezin; Vishnu Kaimal; Sam Keene; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (IGARSS, 2017)

On The Extraction of Training Imagery from Very Large Remote Sensing Datasets for Deep Convolutional Segmenatation Networks. - Bohao Huang; Daniel Reichman 002; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (IGARSS, 2018)

Deep Convolutional Segmentation of Remote Sensing Imagery: A Simple and Efficient Alternative to Stitching Output Labels. - Bohao Huang; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (IGARSS, 2018)

Large-Scale Semantic Classification: Outcome of the First Year of Inria Aerial Image Labeling Benchmark. - Bohao Huang; Kangkang Lu 001; Nicolas Audebert; Andrew Khalel; Yuliya Tarabalka; Jordan M. Malof; Alexandre Boulch; Bertrand Le Saux; Leslie M. Collins; Kyle Bradbury; Sébastien Lefèvre; Motaz El-Saban (IGARSS, 2018)

Automated Building Energy Consumption Estimation from Aerial Imagery. - Artem Streltsov; Kyle Bradbury; Jordan M. Malof (IGARSS, 2018)

Semisupervised Adversarial Discriminative Domain Adaptation, with Applicationto Remote Sensing Data. - Rui Wang; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (IGARSS, 2018)

Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery. - Joseph A. Camilo; Rui Wang; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (CoRR, 2018)

Dense labeling of large remote sensing imagery with convolutional neural networks: a simple and faster alternative to stitching output label maps. - Bohao Huang; Daniel Reichman 002; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (CoRR, 2018)

gprHOG: Several Simple Improvements to the Histogram of Oriented Gradients Feature for Threat Detection in Ground-Penetrating Radar. - Daniel Reichman 002; Leslie M. Collins; Jordan M. Malof (CoRR, 2018)

A Large Comparison of Feature-Based Approaches for Buried Target Classification in Forward-Looking Ground-Penetrating Radar. - Joseph A. Camilo; Leslie M. Collins; Jordan M. Malof (IEEE Trans. Geosci. Remote. Sens., 2018)

On Choosing Training and Testing Data for Supervised Algorithms in Ground-Penetrating Radar Data for Buried Threat Detection. - Daniël Reichman 002; Leslie M. Collins; Jordan M. Malof (IEEE Trans. Geosci. Remote. Sens., 2018)

Training a single multi-class convolutional segmentation network using multiple datasets with heterogeneous labels: preliminary results. - Fanjie Kong; Cheng Chen; Bohao Huang; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (IGARSS, 2019)

A simple rotational equivariance loss for generic convolutional segmentation networks: preliminary results. - Kangcheng Lin; Bohao Huang; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (IGARSS, 2019)

Mapping solar array location, size, and capacity using deep learning and overhead imagery. - Jordan M. Malof; Boning Li; Bohao Huang; Kyle Bradbury; Artem Stretslov (CoRR, 2019)

A Large-Scale Multi-Institutional Evaluation of Advanced Discrimination Algorithms for Buried Threat Detection in Ground Penetrating Radar. - Jordan M. Malof; Daniël Reichman 002; Andrew Karem; Hichem Frigui; K. C. Ho 001; Joseph N. Wilson; Wen-Hsiung Lee; William Cummings; Leslie M. Collins (IEEE Trans. Geosci. Remote. Sens., 2019)

Mapping Electric Transmission Line Infrastructure from Aerial Imagery with Deep Learning. - Wei Hu; Ben Alexander; Wendell Cathcart; Atsushi Hu; Varun Nair; Lin Zuo; Jordan M. Malof; Leslie M. Collins; Kyle Bradbury (IGARSS, 2020)

Do Deep Learning Models Generalize to Overhead Imagery from Novel Geographic Domains? The xGD Benchmark Problem. - Bohao Huang; Kyle Bradbury; Leslie M. Collins; Jordan M. Malof (IGARSS, 2020)

Designing Synthetic Overhead Imagery to Match a Target Geographic Region: Preliminary Results Training Deep Learning Models. - Varun Nair; Paul Rhee; Jichen Yang; Bohao Huang; Kyle Bradbury; Jordan M. Malof (IGARSS, 2020)

Benchmarking Deep Inverse Models over time, and the Neural-Adjoint method. - Simiao Ren; Willie Padilla; Jordan M. Malof (NeurIPS, 2020)

The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation. - Fanjie Kong; Bohao Huang; Kyle Bradbury; Jordan M. Malof (WACV, 2020)

Wind Turbine Detection with Synthetic Overhead Imagery. - Wei Hu; Tyler Feldman; Yanchen Jessie Ou; Natalie Tarn; Baoyan Ye; Yang Xu 007; Jordan M. Malof; Kyle Bradbury (IGARSS, 2021)

Application of Compositional Neural Networks for Robust Classification of Infrared Imagery. - Gregory P. Spell; Leslie M. Collins; Jordan M. Malof (IGARSS, 2021)

Benchmarking Data-driven Surrogate Simulators for Artificial Electromagnetic Materials. - Yang Deng; Juncheng Dong; Simiao Ren; Omar Khatib; Mohammadreza Soltani; Vahid Tarokh; Willie Padilla; Jordan M. Malof (NeurIPS Datasets and Benchmarks, 2021)

Randomized Histogram Matching: A Simple Augmentation for Unsupervised Domain Adaptation in Overhead Imagery. - Can Yaris; Bohao Huang; Kyle Bradbury; Jordan M. Malof (CoRR, 2021)

SIMPL: Generating Synthetic Overhead Imagery to Address Zero-shot and Few-Shot Detection Problems. - Yang Xu 007; Bohao Huang; Xiong Luo; Kyle Bradbury; Jordan M. Malof (CoRR, 2021)

Inverse deep learning methods and benchmarks for artificial electromagnetic material design. - Simiao Ren; Ashwin Mahendra; Omar Khatib; Yang Deng; Willie J. Padilla; Jordan M. Malof (CoRR, 2021)

Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions. - Juncheng Dong; Simiao Ren; Yang Deng; Omar Khatib; Jordan M. Malof; Mohammadreza Soltani; Willie Padilla; Vahid Tarokh (ICLR, 2022)

Hyperparameter-free deep active learning for regression problems via query synthesis. - Simiao Ren; Yang Deng; Willie J. Padilla; Jordan M. Malof (CoRR, 2022)

Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis. - Simiao Ren; Wei Hu; Kyle Bradbury; Dylan Harrison-Atlas; Laura Malaguzzi Valeri; Brian Murray; Jordan M. Malof (CoRR, 2022)

Meta-simulation for the Automated Design of Synthetic Overhead Imagery. - Handi Yu; Leslie M. Collins; Jordan M. Malof (CoRR, 2022)

Utilizing Geospatial Data for Assessing Energy Security: Mapping Small Solar Home Systems Using Unmanned Aerial Vehicles and Deep Learning. - Simiao Ren; Jordan M. Malof; Rob Fetter; Robert H. Beach; James Rineer; Kyle Bradbury (ISPRS Int. J. Geo Inf., 2022)

Self-Supervised Encoders Are Better Transfer Learners in Remote Sensing Applications. - Zachary D. Calhoun; Saad Lahrichi; Simiao Ren; Jordan M. Malof; Kyle Bradbury (Remote. Sens., 2022)

GridTracer: Automatic Mapping of Power Grids Using Deep Learning and Overhead Imagery. - Bohao Huang; Jichen Yang; Artem Streltsov; Kyle Bradbury; Leslie M. Collins; Jordan M. Malof (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

SIMPL: Generating Synthetic Overhead Imagery to Address Custom Zero-Shot and Few-Shot Detection Problems. - Yang Xu 007; Bohao Huang; Xiong Luo; Kyle Bradbury; Jordan M. Malof (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling. - Gregory P. Spell; Simiao Ren; Leslie M. Collins; Jordan M. Malof (AAAI, 2023)

Transformers For Recognition In Overhead Imagery: A Reality Check. - Francesco Luzi; Aneesh Gupta; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (WACV, 2023)

Deep Active Learning for Scientific Computing in the Wild. - Simiao Ren; Yang Deng; Willie J. Padilla; Leslie M. Collins; Jordan M. Malof (CoRR, 2023)

Deep Generalized Green's Functions. - Rixi Peng; Juncheng Dong; Jordan M. Malof; Willie J. Padilla; Vahid Tarokh (CoRR, 2023)

Enhanced Remote Sensing Model Performance Through Self-Supervised Learning with Multi-Spectral Data. - Marlyne Hakizimana; Emelia Mavis; Yuting Chiu; Jordan M. Malof; Kyle Bradbury (IGARSS, 2024)

Segment anything, from space? - Simiao Ren; Francesco Luzi; Saad Lahrichi; Kaleb Kassaw; Leslie M. Collins; Kyle Bradbury; Jordan M. Malof (WACV, 2024)

Can Large Language Models Learn the Physics of Metamaterials? An Empirical Study with ChatGPT. - Darui Lu; Yang Deng; Jordan M. Malof; Willie J. Padilla (CoRR, 2024)

Randomized Histogram Matching: A Simple Augmentation for Unsupervised Domain Adaptation in Overhead Imagery. - Can Yaras; Kaleb Kassaw; Bohao Huang; Kyle Bradbury; Jordan M. Malof (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

Meta-Learning for Color-to-Infrared Cross-Modal Style Transfer. - Evelyn A. Stump; Francesco Luzi; Leslie M. Collins; Jordan M. Malof (WACV, 2025)

Learning Electromagnetic Metamaterial Physics With ChatGPT. - Darui Lu; Yang Deng; Jordan M. Malof; Willie J. Padilla (IEEE Access, 2025)

Deep generalized Green's function. - Rixi Peng; Juncheng Dong; Jordan M. Malof; Willie J. Padilla; Vahid Tarokh (J. Comput. Phys., 2025)

Is Self-Supervised Pre-training on Satellite Imagery Better than ImageNet? A Systematic Study with Sentinel-2. - Saad Lahrichi; Zion Sheng; Shufan Xia; Kyle Bradbury; Jordan M. Malof (CoRR, 2025)

Predicting Next-Day Wildfire Spread with Time Series and Attention. - Saad Lahrichi; Jesse Johnson; Jordan M. Malof (CoRR, 2025)

An Agentic Framework for Autonomous Metamaterial Modeling and Inverse Design. - Darui Lu; Jordan M. Malof; Willie J. Padilla (CoRR, 2025)

Improving and Evaluating Open Deep Research Agents. - Doaa Allabadi; Kyle Bradbury; Jordan M. Malof (CoRR, 2025)

Are deep learning models robust to partial object occlusion in visual recognition tasks? - Kaleb Kassaw; Francesco Luzi; Leslie M. Collins; Jordan M. Malof (Pattern Recognit., 2026)