Shearlet features for registration of remotely sensed multitemporal images. - James M. Murphy; Jacqueline Le Moigne (IGARSS, 2015)

Anisotropic Harmonic Analysis and Integration of Remotely Sensed Data. - James M. Murphy (2015)

Single-Image Superresolution Through Directional Representations. - Wojciech Czaja; James M. Murphy; Daniel Weinberg (CoRR, 2016)

Automatic Image Registration of Multimodal Remotely Sensed Data With Global Shearlet Features. - James M. Murphy; Jacqueline Le Moigne; David J. Harding (IEEE Trans. Geosci. Remote. Sens., 2016)

Unsupervised Geometric Learning of Hyperspectral Images. - James M. Murphy; Mauro Maggioni (CoRR, 2017)

Iterative active learning with diffusion geometry for hyperspectral images. - James M. Murphy; Mauro Maggioni (WHISPERS, 2018)

Superresolution of Noisy Remotely Sensed Images Through Directional Representations. - Wojciech Czaja; James M. Murphy; Daniel Weinberg (IEEE Geosci. Remote. Sens. Lett., 2018)

Drug-Specific Models Improve the Performance of an EEG-based Automated Brain-State Prediction System. - Kimia Kashkooli; Sam L. Polk; Shubham Chamadia; Eunice Hahm; Breanna Ethridge; Jacob Gitlin; Reine Ibala; Jennifer Mekonnen; Juan Pedemonte; James M. Murphy; Haoqi Sun; M. Brandon Westover; et al. (EMBC, 2019)

Automatic Detection of General Anesthetic-States using ECG-Derived Autonomic Nervous System Features. - Sam L. Polk; Kimia Kashkooli; Sunil Belur Nagaraj; Shubham Chamadia; James M. Murphy; Haoqi Sun; M. Brandon Westover; Riccardo Barbieri; Oluwaseun Akeju (EMBC, 2019)

Unsupervised Discriminative Dimension Reduction for Hyperspectral Chemical Plume Segmentation. - James M. Murphy; Mauro Maggioni (IGARSS, 2019)

Learning by Active Nonlinear Diffusion. - Mauro Maggioni; James M. Murphy (CoRR, 2019)

Learning by Unsupervised Nonlinear Diffusion. - Mauro Maggioni; James M. Murphy (J. Mach. Learn. Res., 2019)

Unsupervised Clustering and Active Learning of Hyperspectral Images With Nonlinear Diffusion. - James M. Murphy; Mauro Maggioni (IEEE Trans. Geosci. Remote. Sens., 2019)

Patch-Based Diffusion Learning for Hyperspectral Image Clustering. - James M. Murphy (IGARSS, 2020)

GLIDE: combining local methods and diffusion state embeddings to predict missing interactions in biological networks. - Kapil Devkota; James M. Murphy; Lenore J. Cowen (Bioinform., 2020)

Manifold Learning and Deep Clustering with Local Dictionaries. - Pranay Tankala; Abiy Tasissa; James M. Murphy; Demba E. Ba (CoRR, 2020)

Path-Based Spectral Clustering: Guarantees, Robustness to Outliers, and Fast Algorithms. - Anna V. Little; Mauro Maggioni; James M. Murphy (J. Mach. Learn. Res., 2020)

Spectral-Spatial Diffusion Geometry for Hyperspectral Image Clustering. - James M. Murphy; Mauro Maggioni (IEEE Geosci. Remote. Sens. Lett., 2020)

Spatially regularized active diffusion learning for high-dimensional images. - James M. Murphy (Pattern Recognit. Lett., 2020)

Multiscale Clustering of Hyperspectral Images Through Spectral-Spatial Diffusion Geometry. - Sam L. Polk; James M. Murphy (IGARSS, 2021)

Deep Diffusion Processes for Active Learning of Hyperspectral Images. - Abiy Tasissa; Duc Nguyen; James M. Murphy (IGARSS, 2021)

A Multiscale Environment for Learning by Diffusion. - James M. Murphy; Sam L. Polk (CoRR, 2021)

CATBOSS: Cluster Analysis of Trajectories Based on Segment Splitting. - Jovan Damjanovic; James M. Murphy; Yu-Shan Lin (J. Chem. Inf. Model., 2021)

Hyperspectral Image Clustering with Spatially-Regularized Ultrametrics. - Shukun Zhang; James M. Murphy (Remote. Sens., 2021)

Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks. - Lenore Cowen; Kapil Devkota; Xiaozhe Hu; James M. Murphy; Kaiyi Wu (SIAM J. Math. Data Sci., 2021)

Measure Estimation in the Barycentric Coding Model. - Matthew Werenski; Ruijie Jiang; Abiy Tasissa; Shuchin Aeron; James M. Murphy (ICML, 2022)

Unsupervised Detection of ASH Dieback Disease (Hymenoscyphus Fraxineus) Using Diffusion-Based Hyperspectral Image Clustering. - Sam L. Polk; Aland H. Y. Chan; Kangning Cui; Robert J. Plemmons; David A. Coomes; James M. Murphy (IGARSS, 2022)

Active Diffusion and VCA-Assisted Image Segmentation of Hyperspectral Images. - Sam L. Polk; Kangning Cui; Robert J. Plemmons; James M. Murphy (IGARSS, 2022)

Unsupervised Spatial-Spectral Hyperspectral Image Reconstruction And Clustering With Diffusion Geometry. - Kangning Cui; Ruoning Li; Sam L. Polk; James M. Murphy; Robert J. Plemmons; Raymond H. Chan (WHISPERS, 2022)

GLIDER: function prediction from GLIDE-based neighborhoods. - Kapil Devkota; Henri Schmidt; Matthew Werenski; James M. Murphy; Mert Erden; Victor Arsenescu; Lenore J. Cowen (Bioinform., 2022)

Diffusion and Volume Maximization-Based Clustering of Highly Mixed Hyperspectral Images. - Sam L. Polk; Kangning Cui; Robert J. Plemmons; James M. Murphy (CoRR, 2022)

Geometric Sparse Coding in Wasserstein Space. - Marshall Mueller; Shuchin Aeron; James M. Murphy; Abiy Tasissa (CoRR, 2022)

Balancing Geometry and Density: Path Distances on High-Dimensional Data. - Anna V. Little; Daniel McKenzie; James M. Murphy (SIAM J. Math. Data Sci., 2022)

Geometrically Regularized Wasserstein Dictionary Learning. - Marshall Mueller; Shuchin Aeron; James M. Murphy; Abiy Tasissa (TAG-ML, 2023)

Estimation of entropy-regularized optimal transport maps between non-compactly supported measures. - Matthew Werenski; James M. Murphy; Shuchin Aeron (CoRR, 2023)

Multivariate Soft Rank via Entropy-Regularized Optimal Transport: Sample Efficiency and Generative Modeling. - Shoaib Bin Masud; Matthew Werenski; James M. Murphy; Shuchin Aeron (J. Mach. Learn. Res., 2023)

K-Deep Simplex: Manifold Learning via Local Dictionaries. - Abiy Tasissa; Pranay Tankala; James M. Murphy; Demba E. Ba (IEEE Trans. Signal Process., 2023)

Unsupervised Diffusion and Volume Maximization-Based Clustering of Hyperspectral Images. - Sam L. Polk; Kangning Cui; Aland H. Y. Chan; David A. Coomes; Robert J. Plemmons; James M. Murphy (Remote. Sens., 2023)

Measuring Segregation via Analysis on Graphs. - Moon Duchin; James M. Murphy; Thomas Weighill (SIAM J. Matrix Anal. Appl., 2023)

Nonlinear Unmixing of Hyperspectral Images via Regularized Wasserstein Dictionary Learning. - Scott Fullenbaum; Marshall Mueller; Abiy Tasissa; James M. Murphy (IGARSS, 2024)

Hyperspectral Image Clustering Via Learned Representation In Wasserstein Space. - Scott Fullenbaum; Marshall Mueller; Abiy Tasissa; James M. Murphy (IGARSS, 2024)

Active Learning for Hyperspectral Images with Regularized Wasserstein Dictionary Learning. - Scott Fullenbaum; James M. Murphy (WHISPERS, 2024)

Learning By Evolving Nonlinear Diffusion for Active Learning on Hyperspectral Images. - Kabir Tripathi; James M. Murphy (WHISPERS, 2024)

Locality Regularized Reconstruction: Structured Sparsity and Delaunay Triangulations. - Marshall Mueller; James M. Murphy; Abiy Tasissa (CoRR, 2024)

Fermat Distances: Metric Approximation, Spectral Convergence, and Clustering Algorithms. - Nicolás García Trillos; Anna V. Little; Daniel McKenzie; James M. Murphy (J. Mach. Learn. Res., 2024)

Superpixel-Based and Spatially Regularized Diffusion Learning for Unsupervised Hyperspectral Image Clustering. - Kangning Cui; Ruoning Li; Sam L. Polk; Yinyi Lin; Hongsheng Zhang 001; James M. Murphy; Robert J. Plemmons; Raymond H. Chan (IEEE Trans. Geosci. Remote. Sens., 2024)

On Rank Energy Statistics via Optimal Transport: Continuity, Convergence, and Change Point Detection. - Matthew Werenski; Shoaib Bin Masud; James M. Murphy; Shuchin Aeron (IEEE Trans. Inf. Theory, 2024)

Synthesis and Analysis of Data as Probability Measures With Entropy-Regularized Optimal Transport. - Brendan Mallery; James M. Murphy; Shuchin Aeron (AISTATS, 2025)

Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and Applications. - Matthew Werenski; Brendan Mallery; Shuchin Aeron; James M. Murphy (AISTATS, 2025)

Gromov-Wasserstein Barycenters: The Analysis Problem. - Rocio Diaz Martin; Ivan Vladimir Medri; James M. Murphy (CoRR, 2025)