Intensity-Based Wasserstein Distance As A Loss Measure For Unsupervised Deformable Deep Registration. - Roozbeh Shams; William Le; Adrien Weihs; Samuel Kadoury (ISBI, 2021)

Material Identification in Complex Environments: Neural Network Approaches to Hyperspectral Image Analysis. - Jason Brown; Bohan Chen; Harris Hardiman-Mostow; Adrien Weihs; Andrea L. Bertozzi; Jocelyn Chanussot (WHISPERS, 2023)

Discrete-to-Continuum Rates of Convergence for $p$-Laplacian Regularization. - Adrien Weihs; Jalal Fadili; Matthew Thorpe (CoRR, 2023)

Consistency of Fractional Graph-Laplacian Regularization in Semisupervised Learning with Finite Labels. - Adrien Weihs; Matthew Thorpe (SIAM J. Math. Anal., 2024)