| PoreFlow-Net: A 3D convolutional neural network to predict fluid flow through porous media JE Santos, D Xu, H Jo, CJ Landry, M Prodanović, MJ Pyrcz Advances in Water Resources 138, 103539, 2020 | 169 | 2020 |
| Evolution of OH and CO-dark molecular gas fraction across a molecular cloud boundary in Taurus D Xu, D Li, N Yue, PF Goldsmith The Astrophysical Journal 819 (1), 22, 2016 | 55 | 2016 |
| CH as a molecular gas tracer and c-shock tracer across a molecular cloud boundary in Taurus D Xu, D Li The Astrophysical Journal 833 (1), 90, 2016 | 31 | 2016 |
| The Milky Way Project second data release: bubbles and bow shocks T Jayasinghe, D Dixon, MS Povich, B Binder, J Velasco, DM Lepore, D Xu, ... Monthly Notices of the Royal Astronomical Society 488 (1), 1141-1165, 2019 | 29 | 2019 |
| Casi: A convolutional neural network approach for shell identification CM Van Oort, D Xu, SSR Offner, RA Gutermuth The Astrophysical Journal 880 (2), 83, 2019 | 27 | 2019 |
| Application of Convolutional Neural Networks to Identify Stellar Feedback Bubbles in CO Emission D Xu, SSR Offner, R Gutermuth, C Van Oort The Astrophysical Journal 890 (1), 64, 2020 | 20 | 2020 |
| Application of Convolutional Neural Networks to Identify Protostellar Outflows in CO Emission D Xu, SSR Offner, R Gutermuth, C Van Oort The Astrophysical Journal 905 (2), 172, 2020 | 16 | 2020 |
| Assessing the performance of a machine learning algorithm in identifying bubbles in dust emission D Xu, SSR Offner The Astrophysical Journal 851 (2), 149, 2017 | 14 | 2017 |
| A Census of Outflow to Magnetic Field Orientations in Nearby Molecular Clouds D Xu, SSR Offner, R Gutermuth, JC Tan The Astrophysical Journal 941 (1), 81, 2022 | 12 | 2022 |
| Where is OH and does it trace the dark molecular gas (DMG)? D Li, N Tang, H Nguyen, JR Dawson, C Heiles, D Xu, Z Pan, ... The Astrophysical Journal Supplement Series 235 (1), 1, 2018 | 10 | 2018 |
| A Census of Protostellar Outflows in Nearby Molecular Clouds D Xu, SSR Offner, R Gutermuth, S Kong, HG Arce The Astrophysical Journal 926 (1), 19, 2022 | 9 | 2022 |
| Quantifying Dark Gas D Li, D Xu, C Heiles, Z Pan, N Tang arXiv preprint arXiv:1503.02496, 2015 | 8 | 2015 |
| Outflows and bubbles in Taurus: Star-formation feedback sufficient to maintain turbulence H Li, D Li, L Qian, D Xu, PF Goldsmith, A Noriega-Crespo, Y Wu, Y Song, ... The Astrophysical Journal Supplement Series 219 (2), 20, 2015 | 7 | 2015 |
| Application of Convolutional Neural Networks to Predict Magnetic Fields’ Directions in Turbulent Clouds D Xu, CY Law, JC Tan The Astrophysical Journal 942 (2), 95, 2023 | 6 | 2023 |
| Denoising diffusion probabilistic models to predict the density of molecular clouds D Xu, JC Tan, CJ Hsu, Y Zhu The Astrophysical Journal 950 (2), 146, 2023 | 4 | 2023 |
| Characterizing effective flow units in a multiscale porous medium JE Santos, D Xu, M Prodanovic, M Pyrcz Earth and Space Science Open Archive ESSOAr, 2020 | 3 | 2020 |
| Numerical Simulation and Completeness Survey of Bubbles in the Taurus and Perseus Molecular Clouds M Liu, D Li, M Krčo, LC Ho, D Xu, H Li The Astrophysical Journal 885 (2), 124, 2019 | 3 | 2019 |
| Disk Wind Feedback from High-mass Protostars. III. Synthetic CO Line Emission D Xu, JC Tan, JE Staff, JP Ramsey, Y Zhang, KEI Tanaka The Astrophysical Journal 966 (1), 117, 2024 | | 2024 |
| Polarized Light from Massive Protoclusters (POLIMAP). I. Dissecting the role of magnetic fields in the massive infrared dark cloud G28. 37+ 0.07 CY Law, JC Tan, R Skalidis, L Morgan, D Xu, FO Alves, AT Barnes, ... arXiv preprint arXiv:2401.11560, 2024 | | 2024 |
| Predicting the Radiation Field of Molecular Clouds Using Denoising Diffusion Probabilistic Models D Xu, SSR Offner, R Gutermuth, MY Grudić, D Guszejnov, PF Hopkins The Astrophysical Journal 958 (1), 97, 2023 | | 2023 |
