| Dynamic updating of numerical model discrepancy using sequential sampling D Calvetti, O Ernst, E Somersalo Inverse Problems 30 (11), 114019, 2014 | 32 | 2014 |
| Learning dynamic Boltzmann distributions as reduced models of spatial chemical kinetics OK Ernst, T Bartol, T Sejnowski, E Mjolsness The Journal of chemical physics 149 (3), 2018 | 12 | 2018 |
| Learning moment closure in reaction-diffusion systems with spatial dynamic Boltzmann distributions OK Ernst, TM Bartol, TJ Sejnowski, E Mjolsness Physical Review E 99 (6), 063315, 2019 | 7 | 2019 |
| Deep learning moment closure approximations using dynamic Boltzmann distributions OK Ernst, T Bartol, T Sejnowski, E Mjolsness arXiv preprint arXiv:1905.12122, 2019 | 3 | 2019 |
| System for automatically logging strength exercise data V Malis, OKKH Ernst US Patent US20220339499A1, 2022 | | 2022 |
| System for measuring, monitoring and displaying physical parameters of exercises on selectorized fitness machines V Malis, OKKH Ernst, NN Hua US Patent US11117018B2, 2021 | | 2021 |
| Physics-based machine learning for modeling stochastic IP3-dependent calcium dynamics OK Ernst, T Bartol, T Sejnowski, E Mjolsness arXiv preprint arXiv:2109.05053, 2021 | | 2021 |
| Supplemental Material to “Deep Learning Moment Closure Approximations using Dynamic Boltzmann Distributions” OK Ernst, T Bartol, T Sejnowski, E Mjolsness | | 2021 |
| Modeling Reaction-Diffusion Systems with Dynamic Boltzmann Distributions OK Ernst University of California, San Diego, 2021 | | 2021 |
| Some Prospects for Artificial Intelligence (Both Numeric and Symbolic) in Multiscale Biophysics E Mjolsness, OK Ernst, TM Bartol, TJ Sejnowski Biophysical Journal 116 (3), 323a, 2019 | | 2019 |
| Hard Probe Observables of Jet Quenching in the Monte Carlo Event Generator JEWEL OKK Ernst | | 2018 |
| Sequential Estimation of Discretization Errors in Inverse Problems O Ernst | | 2014 |
Eric MjolsnessProfessor of Computer Science, University of California IrvineVerified email at uci.edu
