Learning Robust Representations for Computer Vision. - Peng Zheng 002; Aleksandr Y. Aravkin; Jayaraman J. Thiagarajan; Karthikeyan Natesan Ramamurthy (ICCV Workshops, 2017)

Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM. - Germán Abrevaya; Aleksandr Y. Aravkin; Guillermo A. Cecchi; Irina Rish; Pablo Polosecki; Peng Zheng 002; Silvina Ponce Dawson (CoRR, 2018)

Sparse Relaxed Regularized Regression: SR3. - Peng Zheng 002; Travis Askham; Steven L. Brunton; J. Nathan Kutz; Aleksandr Y. Aravkin (CoRR, 2018)

Trimming the $ ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. - Jihun Yun; Peng Zheng 002; Eunho Yang; Aurélie C. Lozano; Aleksandr Y. Aravkin (ICML, 2019)

A Unified Framework for Sparse Relaxed Regularized Regression: SR3. - Peng Zheng 002; Travis Askham; Steven L. Brunton; J. Nathan Kutz; Aleksandr Y. Aravkin (IEEE Access, 2019)

A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data. - Kathleen P. Champion; Peng Zheng 002; Aleksandr Y. Aravkin; Steven L. Brunton; J. Nathan Kutz (IEEE Access, 2020)

Sparse Principal Component Analysis via Variable Projection. - N. Benjamin Erichson; Peng Zheng 002; Krithika Manohar; Steven L. Brunton; J. Nathan Kutz; Aleksandr Y. Aravkin (SIAM J. Appl. Math., 2020)

Trimmed Constrained Mixed Effects Models: Formulations and Algorithms. - Peng Zheng 002; Ryan Barber; Reed J. D. Sorensen; Christopher J. L. Murray; Aleksandr Y. Aravkin (J. Comput. Graph. Stat., 2021)

Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. - Germán Abrevaya; Guillaume Dumas; Aleksandr Y. Aravkin; Peng Zheng 002; Jean-Christophe Gagnon-Audet; James R. Kozloski; Pablo Polosecki; Guillaume Lajoie; David D. Cox; Silvina Ponce Dawson; Guillermo A. Cecchi; Irina Rish (Neural Comput., 2021)

Estimating Shape Parameters of Piecewise Linear-Quadratic Problems. - Peng Zheng 002; Karthikeyan Natesan Ramamurthy; Aleksandr Y. Aravkin (Open J. Math. Optim., 2021)

Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models. - Jonathan Jonker; Peng Zheng 002; Aleksandr Y. Aravkin (IEEE Trans. Autom. Control., 2021)

Robust and Scalable Methods for the Dynamic Mode Decomposition. - Travis Askham; Peng Zheng 002; Aleksandr Y. Aravkin; J. Nathan Kutz (SIAM J. Appl. Dyn. Syst., 2022)

pysr3: A Python Package for Sparse Relaxed Regularized Regression. - Aleksei Sholokhov; Peng Zheng 002; Aleksandr Y. Aravkin (J. Open Source Softw., 2023)

Uncertainty Quantification under Noisy Constraints, with Applications to Raking. - Ariane Ducellier; Alexander Hsu; Parkes Kendrick; Bill Gustafson; Laura Dwyer-Lindgren; Christopher Murray; Peng Zheng 002; Aleksandr Y. Aravkin (CoRR, 2024)

A Relaxation Approach to Feature Selection for Linear Mixed Effects Models. - Aleksei Sholokhov; James V. Burke; Damian F. Santomauro; Peng Zheng 002; Aleksandr Y. Aravkin (J. Comput. Graph. Stat., 2024)