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ORCIDLaurent Callot
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2020 – today
- 2024
[c8]Yefan Tao, Luyang Kong, Andrey Kan, Laurent Callot:
Textual Dataset Distillation via Language Model Embedding. EMNLP (Findings) 2024: 12557-12569- [c7]Gauthier Guinet, Behrooz Omidvar-Tehrani, Anoop Deoras, Laurent Callot:
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation. ICML 2024 - [i15]Jingchao Ni, Gauthier Guinet, Peihong Jiang, Laurent Callot, Andrey Kan:
MELODY: Robust Semi-Supervised Hybrid Model for Entity-Level Online Anomaly Detection with Multivariate Time Series. CoRR abs/2401.10338 (2024) - [i14]Gauthier Guinet, Behrooz Omidvar-Tehrani, Anoop Deoras, Laurent Callot:
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation. CoRR abs/2405.13622 (2024) - [i13]Shou Li, Andrey Kan, Laurent Callot, Bhavana Bhasker, Muhammad Shihab Rashid, Timothy B. Esler:
REDO: Execution-Free Runtime Error Detection for COding Agents. CoRR abs/2410.09117 (2024) - 2023
- [j1]Konstantinos Benidis
, Syama Sundar Rangapuram, Valentin Flunkert, Yuyang Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, François-Xavier Aubet, Laurent Callot, Tim Januschowski:
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. ACM Comput. Surv. 55(6): 121:1-121:36 (2023) - [c6]Mononito Goswami, Cristian I. Challu, Laurent Callot, Lenon Minorics, Andrey Kan:
Unsupervised Model Selection for Time Series Anomaly Detection. ICLR 2023 - 2022
- [c5]Cristian I. Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot:
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. AISTATS 2022: 1643-1654 - [c4]Lenon Minorics, Ali Caner Türkmen, David Kernert, Patrick Blöbaum, Laurent Callot, Dominik Janzing:
Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies. AISTATS 2022: 10534-10554 - [i12]Christian Bock, François-Xavier Aubet, Jan Gasthaus, Andrey Kan, Ming Chen, Laurent Callot:
Online Time Series Anomaly Detection with State Space Gaussian Processes. CoRR abs/2201.06763 (2022) - [i11]Cristian Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot:
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. CoRR abs/2202.07586 (2022) - [i10]Mostafa Rahmani, Anoop Deoras, Laurent Callot:
Robust Projection based Anomaly Extraction (RPE) in Univariate Time-Series. CoRR abs/2205.15548 (2022) - [i9]Mononito Goswami, Cristian Challu, Laurent Callot, Lenon Minorics, Andrey Kan:
Unsupervised Model Selection for Time-series Anomaly Detection. CoRR abs/2210.01078 (2022) - [i8]Cristian Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot:
SpectraNet: Multivariate Forecasting and Imputation under Distribution Shifts and Missing Data. CoRR abs/2210.12515 (2022) - [i7]Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot:
Criteria for Classifying Forecasting Methods. CoRR abs/2212.03523 (2022) - 2021
- [c3]Quentin Rebjock, Baris Kurt, Tim Januschowski, Laurent Callot:
Online false discovery rate control for anomaly detection in time series. NeurIPS 2021: 26487-26498 - [i6]Elena Ehrlich, Laurent Callot, François-Xavier Aubet:
Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time Series. CoRR abs/2106.10952 (2021) - [i5]Quentin Rebjock, Baris Kurt, Tim Januschowski, Laurent Callot:
Online false discovery rate control for anomaly detection in time series. CoRR abs/2112.03196 (2021) - 2020
- [c2]Quentin Rebjock, Valentin Flunkert, Tim Januschowski, Laurent Callot, Joel Castellon:
A Simple and Effective Predictive Resource Scaling Heuristic for Large-scale Cloud Applications. AIDB@VLDB 2020 - [i4]Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Bernie Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, Laurent Callot, Tim Januschowski:
Neural forecasting: Introduction and literature overview. CoRR abs/2004.10240 (2020) - [i3]Valentin Flunkert, Quentin Rebjock, Joel Castellon, Laurent Callot, Tim Januschowski:
A simple and effective predictive resource scaling heuristic for large-scale cloud applications. CoRR abs/2008.01215 (2020) - [i2]Luyang Kong, Lifan Chen, Ming Chen, Parminder Bhatia, Laurent Callot:
Improve black-box sequential anomaly detector relevancy with limited user feedback. CoRR abs/2009.07241 (2020)
2010 – 2019
- 2019
- [c1]David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus:
High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes. NeurIPS 2019: 6824-6834 - [i1]David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus:
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes. CoRR abs/1910.03002 (2019)
Coauthor Index
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