Optimal experiment selection for parameter estimation in biological differential equation models. - Mark K. Transtrum; Peng Qiu (BMC Bioinform., 2012)

A unified view of Balanced Truncation and Singular Perturbation Approximations. - Philip E. Pare; Alma T. Wilson; Mark K. Transtrum; Sean C. Warnick (ACC, 2015)

Information geometry for model verification in energy systems. - Mark K. Transtrum; Andrija T. Saric; Alex M. Stankovic (PSCC, 2016)

Bridging Mechanistic and Phenomenological Models of Complex Biological Systems. - Mark K. Transtrum; Peng Qiu (PLoS Comput. Biol., 2016)

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems. - Andrew White; Malachi Tolman; Howard D. Thames; Hubert Rodney Withers; Kathy A. Mason; Mark K. Transtrum (PLoS Comput. Biol., 2016)

Rational ignorance: simpler models learn more from finite data. - Henry H. Mattingly; Mark K. Transtrum; Michael C. Abbott; Benjamin B. Machta (CoRR, 2017)

Influence of Communication Irregularities and Co-simulation on Hybrid Power System State Estimation. - Vanja G. Svenda; Alex M. Stankovic; Andrija T. Saric; Mark K. Transtrum (ISGT Europe, 2018)

Experimental design and model reduction in systems biology. - Jenny Jeong; Qinwei Zhuang; Mark K. Transtrum; Enlu Zhou; Peng Qiu (Quant. Biol., 2018)

Model Boundary Approximation Method as a Unifying Framework for Balanced Truncation and Singular Perturbation Approximation. - Philip E. Paré; David Grimsman; Alma T. Wilson; Mark K. Transtrum; Sean Warnick (IEEE Trans. Autom. Control., 2019)

Modeling Live Crowd Emotion Dynamics for State Estimation and Prediction. - Brooks A. Butler; Philip E. Paré; Mark K. Transtrum; Sean Warnick (CCTA, 2021)

Piecemeal Reduction of Models of Large Networks. - Benjamin L. Francis; Mark K. Transtrum; Andrija T. Saric; Aleksandar M. Stankovic (CDC, 2021)

Extending OpenKIM with an Uncertainty Quantification Toolkit for Molecular Modeling. - Yonatan Kurniawan; Cody L. Petrie; Mark K. Transtrum; Ellad B. Tadmor; Ryan S. Elliott; Daniel S. Karls; Mingjian Wen (e-Science, 2022)

A Picture of the Space of Typical Learnable Tasks. - Rahul Ramesh; Jialin Mao; Itay Griniasty; Rubing Yang; Han Kheng Teoh; Mark K. Transtrum; James P. Sethna; Pratik Chaudhari (ICML, 2023)

The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold. - Jialin Mao; Itay Griniasty; Han Kheng Teoh; Rahul Ramesh; Rubing Yang; Mark K. Transtrum; James P. Sethna; Pratik Chaudhari (CoRR, 2023)

Integration of Physics- and Data-Driven Power System Models in Transient Analysis After Major Disturbances. - Aleksandar A. Saric; Mark K. Transtrum; Andrija T. Saric; Aleksandar M. Stankovic (IEEE Syst. J., 2023)

Recurrence Quantification Analysis of Crowd Sound Dynamics. - Shannon Proksch; Majerle Reeves; Kent Gee; Mark K. Transtrum; Christopher T. Kello; Ramesh Balasubramaniam (Cogn. Sci., 2023)

Aliasing and Label-Independent Decomposition of Risk: Beyond the bias-variance trade-off. - Mark K. Transtrum; Gus L. W. Hart; Tyler J. Jarvis; Jared P. Whitehead (CoRR, 2024)

An information-matching approach to optimal experimental design and active learning. - Yonatan Kurniawan; Tracianne B. Neilsen; Benjamin L. Francis; Alex M. Stankovic; Mingjian Wen; Ilia A. Nikiforov; Ellad B. Tadmor; Vasily V. Bulatov; Vincenzo Lordi; Mark K. Transtrum (CoRR, 2024)

Comparing analytic and data-driven approaches to parameter identifiability: A power systems case study. - Nikolaos Evangelou; Alexander M. Stankovic; Ioannis G. Kevrekidis; Mark K. Transtrum (CoRR, 2024)

Quantitative and Kinetic Proteomics Reveal ApoE Isoform-dependent Proteostasis Adaptations in Mouse Brain. - Nathan R. Zuniga; Noah E. Earls; Ariel E. A. Denos; Jared M. Elison; Benjamin S. Jones; Ethan G. Smith; Noah G. Moran; Katie L. Broce; Gerome M. Romero; Chad D. Hyer; Kimberly B. Wagstaff; Haifa M. Almughamsi; et al. (PLoS Comput. Biol., 2024)

Open Materials Generation with Stochastic Interpolants. - Philipp Höllmer; Thomas Egg; Maya M. Martirossyan; Eric Fuemmeler; Amit Gupta; Zeren Shui; Pawan Prakash; Adrian Roitberg; Mingjie Liu; George Karypis; Mark K. Transtrum; Richard G. Hennig; et al. (CoRR, 2025)

Composable and adaptive design of machine learning interatomic potentials guided by Fisher-information analysis. - Weishi Wang; Mark K. Transtrum; Vincenzo Lordi; Vasily V. Bulatov; Amit Samanta 003 (CoRR, 2025)

An Analytical Characterization of Sloppiness in Neural Networks: Insights from Linear Models. - Jialin Mao; Itay Griniasty; Yan Sun; Mark K. Transtrum; James P. Sethna; Pratik Chaudhari (CoRR, 2025)