no code implementations • 6 Dec 2023 • Iain Rolland, Sivasakthy Selvakumaran, Andrea Marinoni
Referred to as GraphProp, the method propagates observed entries around a graph-based representation of the tensor in order to recover the missing entries.
no code implementations • 29 Nov 2023 • Andrea Marinoni, Pietro Lio', Alessandro Barp, Christian Jutten, Mark Girolami
The reliability of graph embeddings directly depends on how much the geometry of the continuous space matches the graph structure.
no code implementations • 7 Dec 2021 • Andrea Marinoni, Christian Jutten, Mark Girolami
This system provides several constraints and assumptions on the data properties that might be not valid for multimodal data analysis, especially when large scale datasets collected from heterogeneous sources are considered, so that the accuracy and robustness of the outcomes might be severely jeopardized.
no code implementations • 6 Aug 2021 • Qian Shi, Xiaolei Qin, Lingyu Sun, Zitao Shen, Xiaoping Liu, Xiaocong Xu, Jiaxin Tian, Rong Liu, Andrea Marinoni
To provide guidelines for users and producers, it is urgent to produce a validation sample set at the global level.
no code implementations • 8 May 2021 • Andrea Marinoni, Saloua Chlaily, Eduard Khachatrian, Torbjørn Eltoft, Sivasakthy Selvakumaran, Mark Girolami, Christian Jutten
Nonetheless, when applied to multimodal datasets (i. e., datasets acquired by means of multiple sensing techniques or strategies), the state-of-theart methods for ensemble learning and transfer learning might show some limitations.
1 code implementation • 27 Feb 2021 • Mengxi Liu, Qian Shi, Andrea Marinoni, Da He, Xiaoping Liu, Liangpei Zhang
The experimental results demonstrate the superiority of the proposed method, which not only outperforms all baselines -with the highest F1 scores of 87. 40% on the building change detection dataset and 92. 94% on the change detection dataset -but also obtains the best accuracies on experiments performed with images having a 4x and 8x resolution difference.