Crossing the Streams: Fuzz testing with user input. - Joseph A. Cottam; Leslie M. Blaha; Dimitri Zarzhitsky; Mathew Thomas; Elliott Skomski (IEEE BigData, 2017)

Spectral Analysis and Stability of Deep Neural Dynamics. - Ján Drgona; Elliott Skomski; Soumya Vasisht; Aaron Tuor; Draguna L. Vrabie (CoRR, 2020)

Physics-Informed Neural State Space Models via Learning and Evolution. - Elliott Skomski; Ján Drgona; Aaron Tuor (CoRR, 2020)

Constrained Block Nonlinear Neural Dynamical Models. - Elliott Skomski; Soumya Vasisht; Colby Wight; Aaron Tuor; Ján Drgona; Draguna L. Vrabie (ACC, 2021)

Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution. - Elliott Skomski; Ján Drgona; Aaron Tuor (L4DC, 2021)

Prototypical Region Proposal Networks for Few-Shot Localization and Classification. - Elliott Skomski; Aaron Tuor; Andrew Avila; Lauren A. Phillips; Zachary New; Henry Kvinge; Courtney D. Corley; Nathan O. Hodas (CoRR, 2021)

One Representation to Rule Them All: Identifying Out-of-Support Examples in Few-shot Learning with Generic Representations. - Henry Kvinge; Scott Howland; Nico Courts; Lauren A. Phillips; John Buckheit; Zachary New; Elliott Skomski; Jung H. Lee; Sandeep Tiwari; Jessica Hibler; Courtney D. Corley; Nathan O. Hodas (CoRR, 2021)

Deep Learning Explicit Differentiable Predictive Control Laws for Buildings. - Ján Drgona; Aaron Tuor; Soumya Vasisht; Elliott Skomski; Draguna L. Vrabie (CoRR, 2021)

Adaptive Transfer Learning: a simple but effective transfer learning. - Jung H. Lee; Henry J. Kvinge; Scott Howland; Zachary New; John Buckheit; Lauren A. Phillips; Elliott Skomski; Jessica Hibler; Courtney D. Corley; Nathan O. Hodas (CoRR, 2021)

Neuro-physical dynamic load modeling using differentiable parametric optimization. - Shrirang Abhyankar; Ján Drgona; Andrew August; Elliott Skomski; Aaron Tuor (CoRR, 2022)