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Federico Raimondo
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2020 – today
- 2024
- [c3]Federico Raimondo, Georgios Antonopoulos, Simon B. Eickhoff, Kaustubh R. Patil:
FastGPR: Divide-and-Conquer Technique in Neuroimaging Data Shortens Training Time and Improves Accuracy. ISBI 2024: 1-4 - 2023
- [j6]Andrea I. Luppi
, Joana Cabral
Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness. NeuroImage 275: 120162 (2023) - [j5]Georgios Antonopoulos
A systematic comparison of VBM pipelines and their application to age prediction. NeuroImage 279: 120292 (2023) - [i2]Sami Hamdan, Shammi More, Leonard Sasse
Julearn: an easy-to-use library for leakage-free evaluation and inspection of ML models. CoRR abs/2310.12568 (2023) - [i1]Leonard Sasse, Eliana Nicolaisen-Sobesky, Juergen Dukart, Simon B. Eickhoff, Michael Götz, Sami Hamdan, Vera Komeyer, Abhijit Kulkarni, Juha Lahnakoski, Bradley C. Love, Federico Raimondo, Kaustubh R. Patil:
On Leakage in Machine Learning Pipelines. CoRR abs/2311.04179 (2023) - 2022
- [j4]Mélanie Strauss
Predicting the loss of responsiveness when falling asleep in humans. NeuroImage 251: 119003 (2022) - 2021
- [j3]Riku Ihalainen
How hot is the hot zone? Computational modelling clarifies the role of parietal and frontoparietal connectivity during anaesthetic-induced loss of consciousness. NeuroImage 231: 117841 (2021)
2010 – 2019
- 2018
- [b1]Federico Raimondo:
Standardisation and automatisation of the diagnosis of patients with disorders of consciousness: a machine learning approach applied to electrophysiological brain and body signals. University of Liège, Belgium, 2018 - 2017
- [j2]Mainak Jas
Autoreject: Automated artifact rejection for MEG and EEG data. NeuroImage 159: 417-429 (2017) - 2016
- [c2]Mainak Jas
Automated rejection and repair of bad trials in MEG/EEG. PRNI 2016: 1-4 - 2012
- [j1]Federico Raimondo
CUDAICA: GPU Optimization of Infomax-ICA EEG Analysis. Comput. Intell. Neurosci. 2012: 206972:1-206972:8 (2012) - [c1]A. Kai Qin
An improved CUDA-based implementation of differential evolution on GPU. GECCO 2012: 991-998
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