| Chronos: Learning the language of time series AF Ansari, L Stella, C Turkmen, X Zhang, P Mercado, H Shen, O Shchur, ... arXiv preprint arXiv:2403.07815, 2024 | 780 | 2024 |
| Deep Learning for Time Series Forecasting: Tutorial and Literature Survey K Benidis, SS Rangapuram, V Flunkert, Y Wang, D Maddix, C Turkmen, ... ACM Computing Surveys (CSUR), 2018 | 565* | 2018 |
| GluonTS: Probabilistic and Neural Time Series Modeling in Python A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ... Journal of Machine Learning Research 21 (116), 1-6, 2020 | 507* | 2020 |
| Deep factors for forecasting Y Wang, A Smola, D Maddix, J Gasthaus, D Foster, T Januschowski International conference on machine learning, 6607-6617, 2019 | 273 | 2019 |
| Domain adaptation for time series forecasting via attention sharing X Jin, Y Park, D Maddix, H Wang, Y Wang International Conference on Machine Learning, 10280-10297, 2022 | 143 | 2022 |
| Prediff: Precipitation nowcasting with latent diffusion models Z Gao, X Shi, B Han, H Wang, X Jin, D Maddix, Y Zhu, M Li, YB Wang Advances in Neural Information Processing Systems 36, 78621-78656, 2023 | 140 | 2023 |
| First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting X Zhang, X Jin, K Gopalswamy, G Gupta, Y Park, X Shi, H Wang, ... NeurIPS'22 Workshop on All Things Attention: Bridging Different Perspectives …, 2022 | 88 | 2022 |
| Bridging physics-based and data-driven modeling for learning dynamical systems R Wang, D Maddix, C Faloutsos, Y Wang, R Yu Learning for dynamics and control, 385-398, 2021 | 82 | 2021 |
| Learning Physical Models that Can Respect Conservation Laws D Hansen, DC Maddix, S Alizadeh, G Gupta, MW Mahoney Physica D: Nonlinear Phenomena 457 (133952), 2024 | 77 | 2024 |
| Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting Y Park, D Maddix, FX Aubet, K Kan, J Gasthaus, Y Wang International Conference on Artificial Intelligence and Statistics 151, 8127 …, 2022 | 75 | 2022 |
| Early warning of complex climate risk with integrated artificial intelligence M Reichstein, V Benson, J Blunk, G Camps-Valls, F Creutzig, CJ Fearnley, ... Nature Communications 16 (1), 2564, 2025 | 59 | 2025 |
| Deep factors with gaussian processes for forecasting DC Maddix, Y Wang, A Smola arXiv preprint arXiv:1812.00098, 2018 | 57 | 2018 |
| Guiding continuous operator learning through Physics-based boundary constraints N Saad, G Gupta, S Alizadeh, DC Maddix International Conference on Learning Representations, 2023 | 36 | 2023 |
| DrivAerML: High-fidelity computational fluid dynamics dataset for road-car external aerodynamics N Ashton, C Mockett, M Fuchs, L Fliessbach, H Hetmann, T Knacke, ... arXiv preprint arXiv:2408.11969, 2024 | 26 | 2024 |
| AhmedML: High-fidelity computational fluid dynamics dataset for incompressible, low-speed bluff body aerodynamics N Ashton, DC Maddix, S Gundry, PM Shabestari arXiv preprint arXiv:2407.20801, 2024 | 17 | 2024 |
| Numerical Artifacts in the Generalized Porous Medium Equation: Why Harmonic Averaging Itself Is Not to Blame D Maddix, M Gerritsen, L Sampaio Journal of Computational Physics 361, 280-298, 2018 | 17 | 2018 |
| Using uncertainty quantification to characterize and improve out-of-domain learning for pdes SC Mouli, DC Maddix, S Alizadeh, G Gupta, A Stuart, MW Mahoney, ... arXiv preprint arXiv:2403.10642, 2024 | 16 | 2024 |
| Enhancing foundation models for time series forecasting via Wavelet-based tokenization L Masserano, AF Ansari, B Han, X Zhang, C Faloutsos, MW Mahoney, ... arXiv preprint arXiv:2412.05244, 2024 | 14 | 2024 |
| Gradient-free generation for hard-constrained systems C Cheng, B Han, DC Maddix, AF Ansari, A Stuart, MW Mahoney, Y Wang arXiv preprint arXiv:2412.01786, 2024 | 13 | 2024 |
| Advanced Fluid Reduced Order Models for Compressible Flow. IK Tezaur, JA Fike, KT Carlberg, MF Barone, D Maddix, EE Mussoni, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2017 | 12 | 2017 |
