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| AI Feynman: a Physics-Inspired Method for Symbolic Regression | May 27, 2019 | regressionSymbolic Regression | CodeCode Available | 1 | 5 |
| AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity | Jun 18, 2020 | regressionSymbolic Regression | CodeCode Available | 1 | 5 |
| Deep Ordinal Regression Network for Monocular Depth Estimation | Jun 6, 2018 | Depth EstimationMonocular Depth Estimation | CodeCode Available | 1 | 5 |
| Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey | Feb 6, 2023 | Activity RecognitionClassification | CodeCode Available | 1 | 5 |
| DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing | Oct 14, 2021 | Fault Detectionregression | CodeCode Available | 1 | 5 |
| Deep Ordinal Regression with Label Diversity | Jun 29, 2020 | Age EstimationDiversity | CodeCode Available | 1 | 5 |
| AI-Aristotle: A Physics-Informed framework for Systems Biology Gray-Box Identification | Sep 29, 2023 | parameter estimationregression | CodeCode Available | 1 | 5 |
| An Analysis of Linear Time Series Forecasting Models | Mar 21, 2024 | Formregression | CodeCode Available | 1 | 5 |
| A Mathematical Analysis of Learning Loss for Active Learning in Regression | Apr 19, 2021 | Active LearningPose Estimation | CodeCode Available | 1 | 5 |
