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Nicola Gnecco
Nicola Gnecco
Lecturer in Statistics, Imperial College London
Verified email at imperial.ac.uk - Homepage
Title
Cited by
Cited by
Year
A causal framework for distribution generalization
R Christiansen, N Pfister, ME Jakobsen, N Gnecco, J Peters
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (10), 6614 ¡K, 2021
852021
Causal discovery in heavy-tailed models
N Gnecco, N Meinshausen, J Peters, S Engelke
The Annals of Statistics 49 (3), 1755-1778, 2021
732021
Extremal random forests
N Gnecco, EM Terefe, S Engelke
Journal of the American Statistical Association 119 (548), 3059-3072, 2024
332024
Gastric cancer with positive peritoneal cytology: survival benefit after induction chemotherapy and conversion to negative peritoneal cytology
M Valletti, D Eshmuminov, N Gnecco, CA Gutschow, PM Schneider, ...
World Journal of Surgical Oncology 19, 1-8, 2021
322021
graphicalExtremes: Statistical methodology for graphical extreme value models
S Engelke, AS Hitz, N Gnecco, M Hentschel
R package version 0.1. 0, 2019
21*2019
Boosted control functions
N Gnecco, J Peters, S Engelke, N Pfister
arXiv preprint arXiv:2310.05805, 2023
22023
Extremes of structural causal models
S Engelke, N Gnecco, F Röttger
arXiv preprint arXiv:2503.06536, 2025
2025
Achievable distributional robustness when the robust risk is only partially identified
J Kostin, N Gnecco, F Yang
Advances in Neural Information Processing Systems 37, 83915-83950, 2024
2024
Causal Inference for Extremes
N Gnecco
University of Geneva, 2022
2022
Package 'NILE'
R Christiansen, N Pfister, ME Jakobsen, N Gnecco, J Peters
https://runesen.github.io/NILE/, 2020
2020
Package 'causalXtreme'
N Gnecco, N Meinshausen, J Peters, S Engelke
https://nicolagnecco.github.io/causalXtreme/, 2019
2019
Causality in Heavy-Tailed Data
N Gnecco
ETH Zurich, 2018
2018
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Articles 1–12