Nonlinear Dyanmics in Biological Systems: Actin Networks and Gene Networks. - Andrew Pomerance (2009)

Developing a Stochastic Dynamic Programming Framework for Optical Tweezer-Based Automated Particle Transport Operations. - Ashis Gopal Banerjee; Andrew Pomerance; Wolfgang Losert; Satyandra K. Gupta (IEEE Trans Autom. Sci. Eng., 2010)

Transient Response of Hybrid Boolean Networks as Physical Unclonable Functions. - Daniel Canaday; Noeloikeau F. Charlot; Andrew Pomerance; Daniel J. Gauthier (CoRR, 2019)

Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computers. - Aaron Griffith; Andrew Pomerance; Daniel J. Gauthier (CoRR, 2019)

Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems. - Alexander Wikner; Jaideep Pathak; Brian R. Hunt; Michelle Girvan; Troy Arcomano; Istvan Szunyogh; Andrew Pomerance; Edward Ott (CoRR, 2020)

Model-Free Control of Dynamical Systems with Deep Reservoir Computing. - Daniel Canaday; Andrew Pomerance; Daniel J. Gauthier (CoRR, 2020)

Unconditional Authentication for Constrained Applications via Strong PUFs. - Ahmed S. Bendary; C. Emre Koksal; Daniel Canaday; Andrew Pomerance (CNS, 2021)

Hybrid Boolean Networks as Physically Unclonable Functions. - Noeloikeau F. Charlot; Daniel Canaday; Andrew Pomerance; Daniel J. Gauthier (IEEE Access, 2021)

High-Resolution Waveform Capture Device on a Cyclone-V FPGA. - Noeloikeau F. Charlot; Daniel J. Gauthier; Andrew Pomerance (IEEE Access, 2021)

A Meta-learning Approach to Reservoir Computing: Time Series Prediction with Limited Data. - Daniel Canaday; Andrew Pomerance; Michelle Girvan (CoRR, 2021)

A Novel Attack on Machine-Learning Resistant Physical Unclonable Functions. - Daniel Canaday; Wendson A. S. Barbosa; Andrew Pomerance (HOST, 2022)

Mathematical Model of Strong Physically Unclonable Functions Based on Hybrid Boolean Networks. - Noeloikeau F. Charlot; Daniel J. Gauthier; Daniel Canaday; Andrew Pomerance (HOST, 2022)

Estimating the Unpredictability of Multi-Bit Strong PUF Classes. - Ahmed S. Bendary; Wendson A. S. Barbosa; Andrew Pomerance; C. Emre Koksal (IACR Cryptol. ePrint Arch., 2024)

Stabilizing machine learning prediction of dynamics: Novel noise-inspired regularization tested with reservoir computing. - Alexander Wikner; Joseph Harvey; Michelle Girvan; Brian R. Hunt; Andrew Pomerance; Thomas M. Antonsen Jr.; Edward Ott (Neural Networks, 2024)

Tailored Forecasting from Short Time Series via Meta-learning. - Declan A. Norton; Edward Ott; Andrew Pomerance; Brian R. Hunt; Michelle Girvan (CoRR, 2025)