| Machine learning for the geosciences: Challenges and opportunities A Karpatne, I Ebert-Uphoff, S Ravela, HA Babaie, V Kumar IEEE Transactions on Knowledge and Data Engineering 31 (8), 1544-1554, 2018 | 599 | 2018 |
| Useful metrics for modular robot motion planning A Pamecha, I Ebert-Uphoff, GS Chirikjian IEEE Transactions on Robotics and Automation 13 (4), 531-545, 1997 | 363 | 1997 |
| Wrench-feasible workspace generation for cable-driven robots P Bosscher, AT Riechel, I Ebert-Uphoff IEEE Transactions on Robotics 22 (5), 890-902, 2006 | 360 | 2006 |
| Physically interpretable neural networks for the geosciences: Applications to earth system variability BA Toms, EA Barnes, I Ebert‐Uphoff Journal of Advances in Modeling Earth Systems 12 (9), e2019MS002002, 2020 | 317 | 2020 |
| Causal discovery for climate research using graphical models I Ebert-Uphoff, Y Deng Journal of Climate 25 (17), 5648-5665, 2012 | 244 | 2012 |
| Evaluating efficiency of self‐reconfiguration in a class of modular robots G Chirikjian, A Pamecha, I Ebert‐Uphoff Journal of robotic systems 13 (5), 317-338, 1996 | 215 | 1996 |
| Wrench-based analysis of cable-driven robots P Bosscher, I Ebert-Uphoff IEEE International Conference on Robotics and Automation, 2004. Proceedings …, 2004 | 201 | 2004 |
| On the connections between cable-driven robots, parallel manipulators and grasping I Ebert-Uphoff, PA Voglewede IEEE International Conference on Robotics and Automation, 2004. Proceedings …, 2004 | 171 | 2004 |
| Inverse kinematics of discretely actuated hyper-redundant manipulators using workspace densities I Ebert-Uphoff, GS Chirikjian Proceedings of IEEE International Conference on Robotics and Automation 1 …, 1996 | 155 | 1996 |
| Force-feasible workspace analysis for underconstrained, point-mass cable robots AT Riechel, I Ebert-Uphoff IEEE International Conference on Robotics and Automation, 2004. Proceedings …, 2004 | 151 | 2004 |
| Static balancing of spatial parallel platform mechanisms—revisited I Ebert-Uphoff, CM Gosselin, T Laliberte J. Mech. Des. 122 (1), 43-51, 2000 | 132 | 2000 |
| Viewing forced climate patterns through an AI lens EA Barnes, JW Hurrell, I Ebert‐Uphoff, C Anderson, D Anderson Geophysical Research Letters 46 (22), 13389-13398, 2019 | 122 | 2019 |
| Intelligent systems for geosciences: an essential research agenda Y Gil, SA Pierce, H Babaie, A Banerjee, K Borne, G Bust, M Cheatham, ... Communications of the ACM 62 (1), 76-84, 2018 | 114 | 2018 |
| Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscience A Mamalakis, EA Barnes, I Ebert-Uphoff Artificial Intelligence for the Earth Systems 1 (4), e220012, 2022 | 113 | 2022 |
| Tetrad—a toolbox for causal discovery JD Ramsey, K Zhang, M Glymour, RS Romero, B Huang, I Ebert-Uphoff, ... 8th international workshop on climate informatics, 1-4, 2018 | 110 | 2018 |
| Indicator patterns of forced change learned by an artificial neural network EA Barnes, B Toms, JW Hurrell, I Ebert‐Uphoff, C Anderson, D Anderson Journal of Advances in Modeling Earth Systems 12 (9), e2020MS002195, 2020 | 104 | 2020 |
| Evaluation, tuning and interpretation of neural networks for working with images in meteorological applications I Ebert-Uphoff, K Hilburn Bulletin of the American Meteorological Society, 1-47, 2020 | 99 | 2020 |
| Numerical convolution on the Euclidean group with applications to workspace generation GS Chirikjian, I Ebert-Uphoff IEEE Transactions on Robotics and Automation 14 (1), 123-136, 1998 | 99 | 1998 |
| Efficient workspace generation for binary manipulators with many actuators I Ebert‐uphoff, GS Chirikjian Journal of Robotic Systems 12 (6), 383-400, 1995 | 97 | 1995 |
| Why we need to focus on developing ethical, responsible, and trustworthy artificial intelligence approaches for environmental science A McGovern, I Ebert-Uphoff, DJ Gagne II, A Bostrom Environmental Data Science 1, e6, 2022 | 96 | 2022 |
