Adrien Weihs

According to our database, Adrien Weihs authored at least 8 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Higher-Order Regularization Learning on Hypergraphs.

Adrien Weihs, Andrea L. Bertozzi, Matthew Thorpe

CoRR, October, 2025

Topology-Aware Active Learning on Graphs.

Harris Hardiman-Mostow, Jack Mauro, Adrien Weihs, Andrea L. Bertozzi

CoRR, October, 2025

A Deep Learning Framework for Multi-Operator Learning: Architectures and Approximation Theory.

Adrien Weihs, Jingmin Sun, Zecheng Zhang, Hayden Schaeffer

CoRR, October, 2025

Analysis of Semi-Supervised Learning on Hypergraphs.

Adrien Weihs, Andrea L. Bertozzi, Matthew Thorpe

CoRR, October, 2025

2024

Consistency of Fractional Graph-Laplacian Regularization in Semisupervised Learning with Finite Labels.

Adrien Weihs, Matthew Thorpe

SIAM J. Math. Anal., 2024

2023

Discrete-to-Continuum Rates of Convergence for $p$-Laplacian Regularization.

Adrien Weihs, Jalal Fadili, Matthew Thorpe

CoRR, 2023

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

Proceedings of the 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2023

2021

Intensity-Based Wasserstein Distance As A Loss Measure For Unsupervised Deformable Deep Registration.

Roozbeh Shams, William Le, Adrien Weihs, Samuel Kadoury

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021