| NHITS: Neural hierarchical interpolation for time series forecasting C Challu, KG Olivares, BN Oreshkin, F Garza, M Mergenthaler-Canseco, ... AAAI 2023, 2022 | 458 | 2022 |
| TimeGPT-1 A Garza, C Challu, M Mergenthaler-Canseco arXiv preprint arXiv:2310.03589, 2023 | 163 | 2023 |
| 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 | 157 | 2023 |
| StatsForecast: Lightning fast forecasting with statistical and econometric models F Garza, MM Canseco, C Challú, KG Olivares PyCon: Salt Lake City, UT, USA, 2022 | 59 | 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 | 46 | 2022 |
| 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 | 40 | 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 | 30 | 2022 |
| The quality of vote tallies: Causes and consequences C Challú, E Seira, A Simpser American Political Science Review 114 (4), 1071-1085, 2020 | 21 | 2020 |
| HierarchicalForecast: A reference framework for hierarchical forecasting in python KG Olivares, A Garza, D Luo, C Challú, M Mergenthaler, SB Taieb, ... arXiv preprint arXiv:2207.03517, 2022 | 15 | 2022 |
| Proceedings of the AAAI Conference on Artificial Intelligence C Challu, KG Olivares, BN Oreshkin, FG Ramirez, MM Canseco, ... AAAI Press, 2023 | 8 | 2023 |
| 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 | 3 | 2022 |
| 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 | 3 | 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 | 3 | 2021 |
| Hint: Hierarchical mixture networks for coherent probabilistic forecasting KG Olivares, D Luo, C Challu, S La Vattiata, M Mergenthaler, A Dubrawski CoRR, 2023 | 2 | 2023 |
| Forecasting Treatment Response with Deep Pharmacokinetic Encoders W Potosnak, C Challu, KG Olivares, K Dufendach, A Dubrawski ArXiv, arXiv: 2309.13135 v7, 2024 | 1 | 2024 |
| Forecasting Response to Treatment with Deep Learning and Pharmacokinetic Priors W Potosnak, C Challu, KG Olivares, A Dubrawski arXiv preprint arXiv:2309.13135, 2023 | 1 | 2023 |
| Hierarchically Coherent Multivariate Mixture Networks KG Olivares, D Luo, C Challu, S La Vattiata, M Mergenthaler, A Dubrawski arXiv preprint arXiv:2305.07089, 2023 | 1 | 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 | 1 | 2022 |
| Transferability of neural forecast models KG Olivares, C Challu, S La Vattiataa, A Garzab, M Mergenthalerb, ... International Journal of Forecasting, 2024 | | 2024 |
| Implicit Reasoning in Deep Time Series Forecasting W Potosnak, C Challu, M Goswami, M Wiliński, N Żukowska, A Dubrawski arXiv preprint arXiv:2409.10840, 2024 | | 2024 |