| Nonlinear principal component analysis using autoassociative neural networks MA Kramer AIChE journal 37 (2), 233-243, 1991 | 4258 | 1991 |
| Modeling chemical processes using prior knowledge and neural networks ML Thompson, MA Kramer AIChE Journal 40 (8), 1328-1340, 1994 | 817 | 1994 |
| Sensitivity analysis in chemical kinetics H Rabitz, M Kramer, D Dacol Annual review of physical chemistry 34 (1), 419-461, 1983 | 727 | 1983 |
| Autoassociative neural networks MA Kramer Computers & chemical engineering 16 (4), 313-328, 1992 | 664 | 1992 |
| Radial basis function networks for classifying process faults JA Leonard, MA Kramer IEEE Control Systems Magazine 11 (3), 31-38, 1991 | 480 | 1991 |
| Synthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record J Walonoski, M Kramer, J Nichols, A Quina, C Moesel, D Hall, C Duffett, ... Journal of the American Medical Informatics Association 25 (3), 230–238, 2018 | 441 | 2018 |
| Improvement of the backpropagation algorithm for training neural networks J Leonard, MA Kramer Computers & Chemical Engineering 14 (3), 337-341, 1990 | 418 | 1990 |
| A rule‐based approach to fault diagnosis using the signed directed graph MA Kramer, BL Palowitch Jr AIChE journal 33 (7), 1067-1078, 1987 | 412 | 1987 |
| Using radial basis functions to approximate a function and its error bounds JA Leonard, MA Kramer, LH Ungar IEEE transactions on neural networks 3 (4), 624-627, 1992 | 368 | 1992 |
| Diagnosis using backpropagation neural networks—analysis and criticism MA Kramer, JA Leonard Computers & chemical engineering 14 (12), 1323-1338, 1990 | 216 | 1990 |
| A neural network architecture that computes its own reliability JA Leonard, MA Kramer, LH Ungar Computers & chemical engineering 16 (9), 819-835, 1992 | 207 | 1992 |
| Malfunction diagnosis using quantitative models with non‐boolean reasoning in expert systems MA Kramer AIChE Journal 33 (1), 130-140, 1987 | 199 | 1987 |
| A general framework for preventive maintenance optimization in chemical process operations JS Tan, MA Kramer Computers & Chemical Engineering 21 (12), 1451-1469, 1997 | 193 | 1997 |
| The simultaneous solution and sensitivity analysis of systems described by ordinary differential equations JR Leis, MA Kramer ACM Transactions on Mathematical Software (TOMS) 14 (1), 45-60, 1988 | 188 | 1988 |
| Qualitative simulation of chemical process systems: Steady‐state analysis OO Oyeleye, MA Kramer AIChE Journal 34 (9), 1441-1454, 1988 | 162 | 1988 |
| Algorithm 658: ODESSA–an ordinary differential equation solver with explicit simultaneous sensitivity analysis JR Leis, MA Kramer ACM Transactions on Mathematical Software (TOMS) 14 (1), 61-67, 1988 | 146 | 1988 |
| Maximum likelihood data rectification: Steady‐state systems LPM Johnston, MA Kramer AIChE Journal 41 (11), 2415-2426, 1995 | 119 | 1995 |
| An improved computational method for sensitivity analysis: Green's function method with ‘AIM’ MA Kramer, JM Calo, H Rabitz Applied Mathematical Modelling 5 (6), 432-441, 1981 | 105 | 1981 |
| Narrowing diagnostic focus using functional decomposition FE Finch, MA Kramer AIChE Journal 34 (1), 25-36, 1988 | 97 | 1988 |
| Diagnosing dynamic faults using modular neural nets JA Leonard, MA Kramer IEEE Expert 8 (2), 44-53, 1993 | 96 | 1993 |
