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Elliott Skomski
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2020 – today
- 2022
- [i8]Shrirang Abhyankar
, Ján Drgona, Andrew August, Elliott Skomski, Aaron Tuor:
Neuro-physical dynamic load modeling using differentiable parametric optimization. CoRR abs/2203.10582 (2022) - 2021
- [c3]Elliott Skomski, Soumya Vasisht
Constrained Block Nonlinear Neural Dynamical Models. ACC 2021: 3993-4000 - [c2]Elliott Skomski, Ján Drgona, Aaron Tuor:
Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution. L4DC 2021: 980-991 - [i7]Elliott Skomski, Soumya Vasisht, Colby Wight, Aaron Tuor, Ján Drgona, Draguna L. Vrabie:
Constrained Block Nonlinear Neural Dynamical Models. CoRR abs/2101.01864 (2021) - [i6]Elliott Skomski, Aaron Tuor, Andrew Avila, Lauren A. Phillips, Zachary New, Henry Kvinge
Prototypical Region Proposal Networks for Few-Shot Localization and Classification. CoRR abs/2104.03496 (2021) - [i5]Henry Kvinge
One Representation to Rule Them All: Identifying Out-of-Support Examples in Few-shot Learning with Generic Representations. CoRR abs/2106.01423 (2021) - [i4]Ján Drgona, Aaron Tuor, Soumya Vasisht, Elliott Skomski, Draguna L. Vrabie:
Deep Learning Explicit Differentiable Predictive Control Laws for Buildings. CoRR abs/2107.11843 (2021) - [i3]Jung H. Lee, Henry J. Kvinge
Adaptive Transfer Learning: a simple but effective transfer learning. CoRR abs/2111.10937 (2021) - 2020
- [i2]Ján Drgona, Elliott Skomski, Soumya Vasisht, Aaron Tuor, Draguna L. Vrabie:
Spectral Analysis and Stability of Deep Neural Dynamics. CoRR abs/2011.13492 (2020) - [i1]Elliott Skomski, Ján Drgona, Aaron Tuor:
Physics-Informed Neural State Space Models via Learning and Evolution. CoRR abs/2011.13497 (2020)
2010 – 2019
- 2017
- [c1]Joseph A. Cottam, Leslie M. Blaha, Dimitri Zarzhitsky, Mathew Thomas, Elliott Skomski:
Crossing the Streams: Fuzz testing with user input. IEEE BigData 2017: 4362-4371
Coauthor Index
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