High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes. - David Salinas; Michael Bohlke-Schneider; Laurent Callot; Roberto Medico; Jan Gasthaus (NeurIPS, 2019)

A Simple and Effective Predictive Resource Scaling Heuristic for Large-scale Cloud Applications. - Quentin Rebjock; Valentin Flunkert; Tim Januschowski; Laurent Callot; Joel Castellon (AIDB@VLDB, 2020)

Neural forecasting: Introduction and literature overview. - Konstantinos Benidis; Syama Sundar Rangapuram; Valentin Flunkert; Bernie Wang 001; Danielle C. Maddix; Ali Caner Türkmen; Jan Gasthaus; Michael Bohlke-Schneider; David Salinas; Lorenzo Stella; Laurent Callot; Tim Januschowski (CoRR, 2020)

Improve black-box sequential anomaly detector relevancy with limited user feedback. - Luyang Kong; Lifan Chen; Ming Chen; Parminder Bhatia; Laurent Callot (CoRR, 2020)

Online false discovery rate control for anomaly detection in time series. - Quentin Rebjock; Baris Kurt; Tim Januschowski; Laurent Callot (NeurIPS, 2021)

Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time Series. - Elena Ehrlich; Laurent Callot; François-Xavier Aubet (CoRR, 2021)

Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. - Cristian I. Challu; Peihong Jiang; Ying Nian Wu; Laurent Callot (AISTATS, 2022)

Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies. - Lenon Minorics; Ali Caner Türkmen; David Kernert; Patrick Blöbaum; Laurent Callot; Dominik Janzing (AISTATS, 2022)

Online Time Series Anomaly Detection with State Space Gaussian Processes. - Christian Bock; François-Xavier Aubet; Jan Gasthaus; Andrey Kan; Ming Chen; Laurent Callot (CoRR, 2022)

Robust Projection based Anomaly Extraction (RPE) in Univariate Time-Series. - Mostafa Rahmani; Anoop Deoras; Laurent Callot (CoRR, 2022)

SpectraNet: Multivariate Forecasting and Imputation under Distribution Shifts and Missing Data. - Cristian Challu; Peihong Jiang; Ying Nian Wu; Laurent Callot (CoRR, 2022)

Criteria for Classifying Forecasting Methods. - Tim Januschowski; Jan Gasthaus; Yuyang Wang 001; David Salinas; Valentin Flunkert; Michael Bohlke-Schneider; Laurent Callot (CoRR, 2022)

Unsupervised Model Selection for Time Series Anomaly Detection. - Mononito Goswami; Cristian I. Challu; Laurent Callot; Lenon Minorics; Andrey Kan (ICLR, 2023)

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. - Konstantinos Benidis; Syama Sundar Rangapuram; Valentin Flunkert; Yuyang Wang 001; Danielle C. Maddix; Ali Caner Türkmen; Jan Gasthaus; Michael Bohlke-Schneider; David Salinas; Lorenzo Stella; François-Xavier Aubet; Laurent Callot; et al. (ACM Comput. Surv., 2023)

Textual Dataset Distillation via Language Model Embedding. - Yefan Tao; Luyang Kong; Andrey Kan; Laurent Callot (EMNLP (Findings), 2024)

Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation. - Gauthier Guinet; Behrooz Omidvar-Tehrani; Anoop Deoras; Laurent Callot (ICML, 2024)

MELODY: Robust Semi-Supervised Hybrid Model for Entity-Level Online Anomaly Detection with Multivariate Time Series. - Jingchao Ni; Gauthier Guinet; Peihong Jiang; Laurent Callot; Andrey Kan (CoRR, 2024)

REDO: Execution-Free Runtime Error Detection for COding Agents. - Shou Li; Andrey Kan; Laurent Callot; Bhavana Bhasker; Muhammad Shihab Rashid; Timothy B. Esler (CoRR, 2024)

Large Language Model Critics for Execution-Free Evaluation of Code Changes. - Aashish Yadavally; Hoan Nguyen; Laurent Callot; Gauthier Guinet (CoRR, 2025)

SWE-PolyBench: A multi-language benchmark for repository level evaluation of coding agents. - Muhammad Shihab Rashid; Christian Bock; Yuan Zhuang; Alexander Buchholz; Timothy B. Esler; Simon Valentin; Luca Franceschi 003; Martin Wistuba; Prabhu Teja Sivaprasad; Woo Jung Kim; Anoop Deoras; Giovanni Zappella; et al. (CoRR, 2025)