Laurent Callot

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 21

Top Topics

Gaussian Processes

Anomaly Detection

Model Selection

False Discovery Rate

Top Venues

ACM Comput. Surv.

Publications

Gauthier Guinet, Behrooz Omidvar-Tehrani, Anoop Deoras, Laurent Callot
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation. CoRR (2024)
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 (2024)
Mononito Goswami, Cristian I. Challu, Laurent Callot, Lenon Minorics, Andrey Kan
Unsupervised Model Selection for Time Series Anomaly Detection. ICLR (2023)
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) (2023)
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)
Christian Bock, François-Xavier Aubet, Jan Gasthaus, Andrey Kan, Ming Chen, Laurent Callot
Online Time Series Anomaly Detection with State Space Gaussian Processes. CoRR (2022)
Cristian Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. CoRR (2022)
Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot
Criteria for Classifying Forecasting Methods. CoRR (2022)
Cristian Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot
SpectraNet: Multivariate Forecasting and Imputation under Distribution Shifts and Missing Data. CoRR (2022)
Cristian I. Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. AISTATS (2022)
Mostafa Rahmani, Anoop Deoras, Laurent Callot
Robust Projection based Anomaly Extraction (RPE) in Univariate Time-Series. CoRR (2022)
Mononito Goswami, Cristian Challu, Laurent Callot, Lenon Minorics, Andrey Kan
Unsupervised Model Selection for Time-series Anomaly Detection. CoRR (2022)
Quentin Rebjock, Baris Kurt, Tim Januschowski, Laurent Callot
Online false discovery rate control for anomaly detection in time series. NeurIPS (2021)
Elena Ehrlich, Laurent Callot, François-Xavier Aubet
Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time Series. CoRR (2021)
Quentin Rebjock, Baris Kurt, Tim Januschowski, Laurent Callot
Online false discovery rate control for anomaly detection in time series. CoRR (2021)
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)
Luyang Kong, Lifan Chen, Ming Chen, Parminder Bhatia, Laurent Callot
Improve black-box sequential anomaly detector relevancy with limited user feedback. CoRR (2020)
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 (2020)
Valentin Flunkert, Quentin Rebjock, Joel Castellon, Laurent Callot, Tim Januschowski
A simple and effective predictive resource scaling heuristic for large-scale cloud applications. CoRR (2020)
David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes. CoRR (2019)
David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus
High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes. NeurIPS (2019)