Maddix, Danielle C.

18 publications

AISTATS 2025 ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables Sebastian Pineda Arango, Pedro Mercado, Shubham Kapoor, Abdul Fatir Ansari, Lorenzo Stella, Huibin Shen, Hugo Henri Joseph Senetaire, Ali Caner Turkmen, Oleksandr Shchur, Danielle C. Maddix, Michael Bohlke-Schneider, Bernie Wang, Syama Sundar Rangapuram

ICML 2025 Enhancing Foundation Models for Time Series Forecasting via Wavelet-Based Tokenization Luca Masserano, Abdul Fatir Ansari, Boran Han, Xiyuan Zhang, Christos Faloutsos, Michael W. Mahoney, Andrew Gordon Wilson, Youngsuk Park, Syama Sundar Rangapuram, Danielle C. Maddix, Bernie Wang

ICLR 2025 Gradient-Free Generation for Hard-Constrained Systems Chaoran Cheng, Boran Han, Danielle C. Maddix, Abdul Fatir Ansari, Andrew Stuart, Michael W. Mahoney, Bernie Wang

NeurIPS 2025 Mitra: Mixed Synthetic Priors for Enhancing Tabular Foundation Models Xiyuan Zhang, Danielle C. Maddix, Junming Yin, Nick Erickson, Abdul Fatir Ansari, Boran Han, Shuai Zhang, Leman Akoglu, Christos Faloutsos, Michael W. Mahoney, Cuixiong Hu, Huzefa Rangwala, George Karypis, Bernie Wang

TMLR 2024 Chronos: Learning the Language of Time Series Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Turkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Hao Wang, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Bernie Wang

ICLRW 2024 Comparing and Contrasting Deep Learning Weather Prediction Backbones on Navier-Stokes Dynamics Matthias Karlbauer, Danielle C. Maddix, Abdul Fatir Ansari, Boran Han, Gaurav Gupta, Bernie Wang, Andrew Stuart, Michael W. Mahoney

ICML 2024 Transferring Knowledge from Large Foundation Models to Small Downstream Models Shikai Qiu, Boran Han, Danielle C. Maddix, Shuai Zhang, Bernie Wang, Andrew Gordon Wilson

ICML 2024 Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs S Chandra Mouli, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Andrew Stuart, Michael W. Mahoney, Bernie Wang

NeurIPS 2024 WindsorML: High-Fidelity Computational Fluid Dynamics Dataset for Automotive Aerodynamics Neil Ashton, Jordan B. Angel, Aditya S. Ghate, Gaetan K. W. Kenway, Man Long Wong, Cetin Kiris, Astrid Walle, Danielle C. Maddix, Gary Page

ICLR 2023 Guiding Continuous Operator Learning Through Physics-Based Boundary Constraints Nadim Saad, Gaurav Gupta, Shima Alizadeh, Danielle C. Maddix

ICML 2023 Learning Physical Models That Can Respect Conservation Laws Derek Hansen, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Michael W. Mahoney

ICLRW 2023 Learning Physical Models That Can Respect Conservation Laws Derek Hansen, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Michael W. Mahoney

NeurIPSW 2023 PreDiff: Precipitation Nowcasting with Latent Diffusion Models Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Bernie Wang

ICML 2023 Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting Hilaf Hasson, Danielle C. Maddix, Bernie Wang, Gaurav Gupta, Youngsuk Park

NeurIPSW 2022 First De-Trend Then Attend: Rethinking Attention for Time-Series Forecasting Xiyuan Zhang, Xiaoyong Jin, Karthick Gopalswamy, Gaurav Gupta, Youngsuk Park, Xingjian Shi, Hao Wang, Danielle C. Maddix, Bernie Wang

NeurIPSW 2022 Towards Reverse Causal Inference on Panel Data: Precise Formulation and Challenges Jiayao Zhang, Youngsuk Park, Danielle C. Maddix, Dan Roth, Bernie Wang

NeurIPSW 2021 GOPHER: Categorical Probabilistic Forecasting with Graph Structure via Local Continuous-Time Dynamics Ke Alexander Wang, Danielle C. Maddix, Bernie Wang

MLOSS 2020 GluonTS: Probabilistic and Neural Time Series Modeling in Python Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang