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ORCIDMohammed Amine Gharsallaoui
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2020 – today
- 2024
[c4]Mohammed Amine Gharsallaoui, Bhupinderjeet Singh, Supriya Savalkar, Aryan Deshwal, Ananth Kalyanaraman, Kirti Rajagopalan, Janardhan Rao Doppa:
Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach. IJCAI 2024: 7269-7277- [i4]Mohammed Amine Gharsallaoui, Bhupinderjeet Singh, Supriya Savalkar
, Aryan Deshwal, Yan Yan, Ananth Kalyanaraman, Kirti Rajagopalan, Janardhan Rao Doppa:
Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach. CoRR abs/2406.00133 (2024) - 2023
- [j3]Zeynep Gürler, Mohammed Amine Gharsallaoui, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative:
Template-based graph registration network for boosting the diagnosis of brain connectivity disorders. Comput. Medical Imaging Graph. 103: 102140 (2023) - 2022
- [j2]Ahmed Nebli, Mohammed Amine Gharsallaoui, Zeynep Gürler, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative:
Quantifying the reproducibility of graph neural networks using multigraph data representation. Neural Networks 148: 254-265 (2022) - [j1]Nada Chaari, Mohammed Amine Gharsallaoui, Hatice Camgöz-Akdag, Islem Rekik:
Multigraph classification using learnable integration network with application to gender fingerprinting. Neural Networks 151: 250-263 (2022) - 2021
- [c3]Umut Guvercin, Mohammed Amine Gharsallaoui, Islem Rekik:
One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction. PRIME@MICCAI 2021: 25-36 - [c2]Mohammed Amine Gharsallaoui, Furkan Tornaci, Islem Rekik:
Investigating and Quantifying the Reproducibility of Graph Neural Networks in Predictive Medicine. PRIME@MICCAI 2021: 104-116 - [i3]Martin Hanik, Mehmet Arif Demirtas, Mohammed Amine Gharsallaoui, Islem Rekik:
Predicting cognitive scores with graph neural networks through sample selection learning. CoRR abs/2106.09408 (2021) - [i2]Mohammed Amine Gharsallaoui, Islem Rekik:
Quantifying the Reproducibility of Graph Neural Networks using Multigraph Brain Data. CoRR abs/2109.02248 (2021) - [i1]Umut Guvercin, Mohammed Amine Gharsallaoui, Islem Rekik:
One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction. CoRR abs/2110.11238 (2021) - 2020
- [c1]Ugur Demir, Mohammed Amine Gharsallaoui, Islem Rekik:
Clustering-Based Deep Brain MultiGraph Integrator Network for Learning Connectional Brain Templates. UNSURE/GRAIL@MICCAI 2020: 109-120
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