Danielle C. Maddix
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
11
Venues
3
Active years
2019–2025
Best venue rank
A*
Where they publish
Papers
11 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AISTATS | ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables. | Sebastian Pineda Arango, Pedro Mercado, Shubham Kapoor, Abdul Fatir Ansari, Lorenzo Stella, Huibin Shen, Hugo Senetaire, Ali Caner Trkmen, Oleksandr Shchur, Danielle C. Maddix, Michael Bohlke-Schneider, Bernie Wang, Syama Sundar Rangapuram |
| 2025 | ICLR | Gradient-Free Generation for Hard-Constrained Systems. | Chaoran Cheng, Boran Han, Danielle C. Maddix, Abdul Fatir Ansari, Andrew Stuart, Michael W. Mahoney, Bernie Wang |
| 2025 | ICML | 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 |
| 2024 | ICML | 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 |
| 2024 | ICML | Transferring Knowledge From Large Foundation Models to Small Downstream Models. | Shikai Qiu, Boran Han, Danielle C. Maddix, Shuai Zhang, Bernie Wang, Andrew Gordon Wilson |
| 2023 | ICLR | Guiding continuous operator learning through Physics-based boundary constraints. | Nadim Saad, Gaurav Gupta, Shima Alizadeh, Danielle C. Maddix |
| 2023 | ICML | Learning Physical Models that Can Respect Conservation Laws. | Derek Hansen, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Michael W. Mahoney |
| 2023 | ICML | Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting. | Hilaf Hasson, Danielle C. Maddix, Bernie Wang, Gaurav Gupta, Youngsuk Park |
| 2022 | AISTATS | Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting. | Youngsuk Park, Danielle C. Maddix, Franois-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang |
| 2022 | ICML | Domain Adaptation for Time Series Forecasting via Attention Sharing. | Xiaoyong Jin, Youngsuk Park, Danielle C. Maddix, Hao Wang, Yuyang Wang |
| 2019 | ICML | Deep Factors for Forecasting. | Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean P. Foster, Tim Januschowski |