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Josephine Maria Thomas
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2020 – today
- 2024
- [j3]Silvia Beddar-Wiesing
, Giuseppe Alessio D'Inverno
, Caterina Graziani
, Veronica Lachi
, Alice Moallemy-Oureh
, Franco Scarselli
, Josephine Maria Thomas:
Weisfeiler-Lehman goes dynamic: An analysis of the expressive power of Graph Neural Networks for attributed and dynamic graphs. Neural Networks 173: 106213 (2024) - [i7]Mohamed Hassouna, Clara Holzhüter, Pawel Lytaev, Josephine M. Thomas, Bernhard Sick, Christoph Scholz:
Graph Reinforcement Learning in Power Grids: A Survey. CoRR abs/2407.04522 (2024) - 2023
- [j2]Josephine Maria Thomas, Alice Moallemy-Oureh, Silvia Beddar-Wiesing, Clara Holzhüter:
Graph Neural Networks Designed for Different Graph Types: A Survey. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [i6]Josephine M. Thomas, Alice Moallemy-Oureh
, Silvia Beddar-Wiesing
, Clara Holzhüter:
Graph Neural Networks Designed for Different Graph Types: A Survey. CoRR abs/2204.03080 (2022) - [i5]Alice Moallemy-Oureh, Silvia Beddar-Wiesing, Rüdiger Nather, Josephine M. Thomas:
FDGNN: Fully Dynamic Graph Neural Network. CoRR abs/2206.03469 (2022) - [i4]Silvia Beddar-Wiesing, Giuseppe Alessio D'Inverno, Caterina Graziani
, Veronica Lachi
, Alice Moallemy-Oureh
, Franco Scarselli, Josephine Maria Thomas:
Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs. CoRR abs/2210.03990 (2022) - 2021
- [i3]Josephine M. Thomas, Silvia Beddar-Wiesing, Alice Moallemy-Oureh, Rüdiger Nather:
Graph type expressivity and transformations. CoRR abs/2109.10708 (2021)
2010 – 2019
- 2018
- [j1]Claudio Durán, Simone Daminelli, Josephine Maria Thomas, V. Joachim Haupt
, Michael Schroeder, Carlo Vittorio Cannistraci:
Pioneering topological methods for network-based drug-target prediction by exploiting a brain-network self-organization theory. Briefings Bioinform. 19(6): 1183-1202 (2018) - 2017
- [b1]Josephine Maria Thomas:
Complex network embedding in the hyperbolic space using non-linear unsupervised machine learning techniques. Dresden University of Technology, Germany, 2017, pp. 1-145 - 2016
- [i2]Josephine Maria Thomas, Alessandro Muscoloni, Sara Ciucci, Ginestra Bianconi, Carlo Vittorio Cannistraci:
Machine learning meets network science: dimensionality reduction for fast and efficient embedding of networks in the hyperbolic space. CoRR abs/1602.06522 (2016) - 2015
- [i1]Simone Daminelli, Josephine Maria Thomas, Claudio Durán, Carlo Vittorio Cannistraci:
Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks. CoRR abs/1504.07011 (2015)
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last updated on 2024-08-13 21:51 CEST by the dblp team
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