Nonclosedness of the Set of Neural Networks in Sobolev Space. - Scott Mahan; Emily J. King; Alex Cloninger (CoRR, 2020)

Rotating spiders and reflecting dogs: a class conditional approach to learning data augmentation distributions. - Scott Mahan; Henry Kvinge; Tim Doster (CoRR, 2021)

DNA: Dynamic Network Augmentation. - Scott Mahan; Tim Doster; Henry Kvinge (CoRR, 2021)

Nonclosedness of sets of neural networks in Sobolev spaces. - Scott Mahan; Emily J. King; Alex Cloninger (Neural Networks, 2021)

Semi-Supervised Manifold Learning with Complexity Decoupled Chart Autoencoders. - Stefan C. Schonsheck; Scott Mahan; Timo Klock; Alexander Cloninger; Rongjie Lai (CoRR, 2022)

Point Cloud Classification via Deep Set Linearized Optimal Transport. - Scott Mahan; Caroline Moosmüller; Alexander Cloninger (CoRR, 2024)

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain. - Guillermo Bernárdez; Lev Telyatnikov; Marco Montagna; Federica Baccini; Mathilde Papillon; Miquel Ferriol Galmés; Mustafa Hajij; Theodore Papamarkou; Maria Sofia Bucarelli; Olga Zaghen; Johan Mathe; Audun Myers; et al. (CoRR, 2024)

Automating Evaluation of Diffusion Model Unlearning with (Vision-) Language Model World Knowledge. - Eric Yeats; Darryl Hannan; Henry Kvinge; Timothy Doster; Scott Mahan (CoRR, 2025)