A Quasi-Minimal Residual Method for Simultaneous Primal-Dual Solutions and Superconvergent Functional Estimates. - James Lu; David L. Darmofal (SIAM J. Sci. Comput., 2003)

Higher-Dimensional Integration with Gaussian Weight for Applications in Probabilistic Design. - James Lu; David L. Darmofal (SIAM J. Sci. Comput., 2004)

An Automatic Technique to Synthesize Avionics Architecture. - Savio Chau; Van Dang; Joseph Xu; James Lu (AHS, 2006)

Inverse bifurcation analysis: application to simple gene systems. - James Lu; Heinz W. Engl; Peter Schuster 002 (Algorithms Mol. Biol., 2006)

The SBML ODE Solver Library: a native API for symbolic and fast numerical analysis of reaction networks. - Rainer Machné; Andrew Finney; Stefan Müller 009; James Lu; Stefanie Widder; Christoph Flamm (Bioinform., 2006)

Inverse Bifurcation Analysis of a Model for the Mammalian G 1/ S Regulatory Module. - James Lu; Heinz W. Engl; Rainer Machné; Peter Schuster 002 (BIRD, 2007)

Computationally implementable sufficient conditions for the synchronisation of coupled dynamical systems with time delays in the coupling. - Elias August; Yongqiang Wang 001; Francis J. Doyle; James Lu; Heinz Koeppl (ACC, 2011)

Trajectory enclosures for nonlinear systems with uncertain initial conditions and parameters. - Elias August; James Lu; Heinz Koeppl (ACC, 2012)

Mapping behavioral specifications to model parameters in synthetic biology. - Heinz Koeppl; Marc Hafner; James Lu (BMC Bioinform., 2013)

An In-Silico Model of Lipoprotein Metabolism and Kinetics for the Evaluation of Targets and Biomarkers in the Reverse Cholesterol Transport Pathway. - James Lu; Katrin Hübner; M. Nazeem Nanjee; Eliot A. Brinton; Norman A. Mazer (PLoS Comput. Biol., 2014)

Deep Poisson Factor Modeling. - Ricardo Henao; Zhe Gan; James Lu; Lawrence Carin (NIPS, 2015)

Electronic Health Record Analysis via Deep Poisson Factor Models. - Ricardo Henao; James Lu; Joseph E. Lucas; Jeffrey M. Ferranti; Lawrence Carin (J. Mach. Learn. Res., 2016)

Deep learning prediction of patient response time course from early data via neural-pharmacokinetic/pharmacodynamic modeling. - James Lu; Brendan Bender; Jin Y. Jin; Yuanfang Guan (CoRR, 2020)

An in vitro quantitative systems pharmacology approach for deconvolving mechanisms of drug-induced, multilineage cytopenias. - Jennifer L. Wilson; Dan Lu; Nick Corr; Aaron Fullerton; James Lu (PLoS Comput. Biol., 2020)

Computing the Hazard Ratios Associated with Explanatory Variables Using Machine Learning Models of Survival Data. - Sameer Sundrani; James Lu (CoRR, 2021)

Deep learning prediction of patient response time course from early data via neural-pharmacokinetic/pharmacodynamic modelling. - James Lu; Brendan Bender; Jin Y. Jin; Yuanfang Guan (Nat. Mach. Intell., 2021)

Multitask-Guided Self-Supervised Tabular Learning for Patient-Specific Survival Prediction. - You Wu; Omid Bazgir; Yongju Lee; Tommaso Biancalani; James Lu; Ehsan Hajiramezanali (MLCB, 2023)

Explainable Deep Learning for Tumor Dynamic Modeling and Overall Survival Prediction using Neural-ODE. - Mark Laurie; James Lu (CoRR, 2023)

Integration of Graph Neural Network and Neural-ODEs for Tumor Dynamic Prediction. - Omid Bazgir; Zichen Wang; Marc Hafner; James Lu (CoRR, 2023)

From Noise to Signal: Unveiling Treatment Effects from Digital Health Data through Pharmacology-Informed Neural-SDE. - Samira Pakravan; Nikolaos Evangelou; Maxime Usdin; Logan Brooks; James Lu (CoRR, 2024)

Predicting overall survival from tumor dynamics metrics using parametric statistical and machine learning models: application to patients with RET-altered solid tumors. - Erick Velasquez; Nastya Kassir; Sravanthi Cheeti; Denison Kuruvilla; Rucha Sane; Steve Dang; Dale Miles; James Lu (Frontiers Artif. Intell., 2024)