Below is a running list of papers I have authored or coauthored.
Preprints
- Riess, H., Veveakis, M., Zavlanos, M. (2024). Path Signatures and Graph Neural Networks for Slow Earthquake Analysis: Better Together?.
Journal Publications
Battiloro, C., Wang, Z., Riess, H., Di Lorenzo, P., Ribeiro, A. (2023). Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back, in IEEE Transactions on Signal Processing.
Ghrist, R., & Riess, H. (2022). Cellular sheaves of lattices and the Tarski Laplacian, in Homology, Homotopy and Applications, 24(1), 325-345.
Catanzaro, M. J., Curry, J. M., Fasy, B. T., Lazovskis, J., Malen, G., Riess, H., Wang, B., & Zabka, M. (2020). Moduli spaces of morse functions for persistence, in Journal of Applied and Computational Topology, 4(3), 353-385.
Conference Proceedings
Riess, H., Henselman-Petrusek, G., Munger, M., Ghrist, R., Bell, Z., & Zavlanos, M. (2023). Network Preference Dynamics using Lattice Theory, to appear in 2024 American Control Conference, Toronto.
Hayhoe, M., Riess, H., Preciado, V., & Ribeiro, A. (2023). Transferable Hypergraph Neural Networks via Spectral Similarity, in Second Learning on Graphs Conference, virtual.
Riess,H., Munger, M., & Zavlanos, M. (2023). Max-Plus Synchronization in Decentralized Trading Systems, in 2023 IEEE 62nd Confernece on Decision and Control (CDC), Singapore.
Battiloro, C., Wang, Z., Riess, H., Di Lorenzo, P., & Ribeiro, A. (2022). Tangent bundle filters and neural networks: from manifolds to cellular sheaves and back, in 2023 Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Riess, H., Ghrist, R. (2022). Diffusion of information on networked lattices by gossip, in IEEE 61st Conference on Decision and Control (CDC), Cancun, Mexico, 5946-5952.
Riess, H., Kantaros, Y., Pappas, G., & Ghrist, R. (2021). A Temporal logic-based hierarchical network connectivity controller, in 2021 Proceedings of the Conference on Control and its Applications, virtual.
Workshop/Thesis/Other
Riess,H. (2022). Lattice Theory in Multi-Agent Systems. Doctor of Philosophy, University of Pennsylvania.
Riess, H., & Hansen, J. (2020). Multidimensional persistence module classification via lattice-theoretic convolutions. In NeurIPS Workshop on Topological Data Analysis and Beyond.
Parada-Mayorga, A., Riess, H., Ribeiro, A., & Ghrist, R. (2020). Quiver Signal Processing (QSP).