| NHITS: Neural hierarchical interpolation for time series forecasting C Challu, KG Olivares, BN Oreshkin, F Garza, M Mergenthaler-Canseco, ... AAAI 2023, 2022 | 207 | 2022 |
| Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx KG Olivares, C Challu, G Marcjasz, R Weron, A Dubrawski International Journal of Forecasting 39 (2), 884-900, 2023 | 80 | 2023 |
| StatsForecast: Lightning fast forecasting with statistical and econometric models F Garza, MM Canseco, C Challú, KG Olivares PyCon Salt Lake City, Utah, US 2022, 6, 2022 | 24 | 2022 |
| Deep generative model with hierarchical latent factors for time series anomaly detection CI Challu, P Jiang, YN Wu, L Callot International Conference on Artificial Intelligence and Statistics, 1643-1654, 2022 | 18 | 2022 |
| Unsupervised model selection for time-series anomaly detection M Goswami, C Challu, L Callot, L Minorics, A Kan arXiv preprint arXiv:2210.01078, 2022 | 15 | 2022 |
| The quality of vote tallies: Causes and consequences C Challú, E Seira, A Simpser American Political Science Review 114 (4), 1071-1085, 2020 | 13 | 2020 |
| NeuralForecast: User friendly state-of-the-art neural forecasting models KG Olivares, C Challú, F Garza, MM Canseco, A Dubrawski PyCon Salt Lake City, Utah, US 2022, 6, 2022 | 8 | 2022 |
| HierarchicalForecast: A reference framework for hierarchical forecasting in Python KG Olivares, F Garza, D Luo, C Challú, M Mergenthaler, SB Taieb, ... arXiv preprint arXiv:2207.03517, 2022 | 6 | 2022 |
| Hint: Hierarchical mixture networks for coherent probabilistic forecasting KG Olivares, D Luo, C Challu, S La Vattiata, M Mergenthaler, A Dubrawski arXiv preprint arXiv:2305.07089, 2023 | 2 | 2023 |
| DMIDAS: Deep mixed data sampling regression for long multi-horizon time series forecasting C Challu, KG Olivares, G Welter, A Dubrawski arXiv preprint arXiv:2106.05860, 2021 | 2 | 2021 |
| Explosion discrimination using seismic gradiometry and spectral filtering of data C Challu, C Poppeliers, P Punoševac, A Dubrawski Bulletin of the Seismological Society of America 111 (3), 1365-1377, 2021 | 2 | 2021 |
| SpectraNet: multivariate forecasting and imputation under distribution shifts and missing data C Challu, P Jiang, YN Wu, L Callot arXiv preprint arXiv:2210.12515, 2022 | 1 | 2022 |
| Forecasting Response to Treatment with Global Deep Learning and Patient-Specific Pharmacokinetic Priors W Potosnak, C Challu, KG Olivares, A Dubrawski ArXiv, 2023 | | 2023 |
| Forecasting Response to Treatment with Deep Learning and Pharmacokinetic Priors W Potosnak, C Challu, KG Olivares, A Dubrawski arXiv preprint arXiv:2309.13135, 2023 | | 2023 |
| HINT: Hierarchical Coherent Networks For Constrained Probabilistic Forecasting KG Olivares, D Luo, CI Challu, S La Vattiata, MM Canseco, A Dubrawski ICML 2023 Workshop on Structured Probabilistic Inference {\&} Generative …, 2023 | | 2023 |
| Explosion Discrimination Using Seismic Gradiometry and Spectrally Filtered Principal Components: Controlled Field Experiments C Challu, C Poppeliers, P Punoševac, A Dubrawski Bulletin of the Seismological Society of America 112 (6), 3141-3150, 2022 | | 2022 |
| Publication Submission Form C Challu, C Poppeliers, P Punosevac, A Dubrawski, C Vollmer Journal Article, 2021 | | 2021 |
| Using seismic gradiometry and machine learning to discriminate between explosion and earthquake seismic sources C Poppeliers, C Challu, P Punosevac, C Vollmer, A Dubrawski AGU Fall Meeting Abstracts 2020, S053-0018, 2020 | | 2020 |
| Double Adaptive Stochastic Gradient Optimization K Gutierrez, J Li, C Challu, A Dubrawski arXiv preprint arXiv:1811.02525, 2018 | | 2018 |
| WORking papers in Management Science KG Olivares, C Challu, G Marcjasz, R Weron, A Dubrawski | | |
