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ORCIDIndro Spinelli
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2020 – today
- 2024
[j9]Vikas Hassija, Vinay Chamola
, Atmesh Mahapatra, Abhinandan Singal, Divyansh Goel, Kaizhu Huang, Simone Scardapane, Indro Spinelli, Mufti Mahmud, Amir Hussain:
Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence. Cogn. Comput. 16(1): 45-74 (2024)- [j8]Siva Sai, Uday Mittal, Vinay Chamola, Kaizhu Huang, Indro Spinelli, Simone Scardapane, Zhiyuan Tan, Amir Hussain:
Machine Un-learning: An Overview of Techniques, Applications, and Future Directions. Cogn. Comput. 16(2): 482-506 (2024) - [j7]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
A Meta-Learning Approach for Training Explainable Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4647-4655 (2024) - [c6]Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael M. Bronstein, Simone Scardapane, Paolo Di Lorenzo:
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module. ICLR 2024 - [i17]Alessandro Baiocchi, Indro Spinelli, Alessandro Nicolosi, Simone Scardapane:
Adaptive Point Transformer. CoRR abs/2401.14845 (2024) - [i16]Mustafa Hajij, Mathilde Papillon, Florian Frantzen, Jens Agerberg, Ibrahem AlJabea, Rubén Ballester, Claudio Battiloro, Guillermo Bernárdez, Tolga Birdal, Aiden Brent, Peter Chin, Sergio Escalera, Simone Fiorellino, Odin Hoff Gardaa, Gurusankar Gopalakrishnan, Devendra Govil, Josef Hoppe, Maneel Reddy Karri, Jude Khouja, Manuel Lecha, Neal Livesay, Jan Meißner, Soham Mukherjee, Alexander Nikitin, Theodore Papamarkou, Jaro Prílepok, Karthikeyan Natesan Ramamurthy, Paul Rosen, Aldo Guzmán-Sáenz, Alessandro Salatiello, Shreyas N. Samaga, Simone Scardapane, Michael T. Schaub, Luca Scofano, Indro Spinelli, Lev Telyatnikov, Quang Truong, Robin Walters, Maosheng Yang, Olga Zaghen, Ghada Zamzmi, Ali Zia, Nina Miolane:
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains. CoRR abs/2402.02441 (2024) - [i15]Luca Scofano, Alessio Sampieri, Tommaso Campari, Valentino Sacco, Indro Spinelli, Lamberto Ballan, Fabio Galasso:
Following the Human Thread in Social Navigation. CoRR abs/2404.11327 (2024) - [i14]Massimiliano Pappa, Luca Collorone, Giovanni Ficarra, Indro Spinelli, Fabio Galasso:
MoDiPO: text-to-motion alignment via AI-feedback-driven Direct Preference Optimization. CoRR abs/2405.03803 (2024) - [i13]Alessio Sampieri, Alessio Palma, Indro Spinelli, Fabio Galasso:
Length-Aware Motion Synthesis via Latent Diffusion. CoRR abs/2407.11532 (2024) - [i12]Muhammad Rameez Ur Rahman, Jhony H. Giraldo, Indro Spinelli, Stéphane Lathuilière, Fabio Galasso:
OVOSE: Open-Vocabulary Semantic Segmentation in Event-Based Cameras. CoRR abs/2408.09424 (2024) - 2023
- [j6]Indro Spinelli, Riccardo Bianchini, Simone Scardapane:
Drop edges and adapt: A fairness enforcing fine-tuning for graph neural networks. Neural Networks 167: 159-167 (2023) - [j5]Alessio Devoto, Indro Spinelli, Francesca Murabito, Fabrizio Chiovoloni, Riccardo Musmeci, Simone Scardapane:
Reidentification of Objects From Aerial Photos With Hybrid Siamese Neural Networks. IEEE Trans. Ind. Informatics 19(3): 2997-3005 (2023) - [c5]Indro Spinelli, Michele Guerra, Filippo Maria Bianchi, Simone Scardapane:
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability. ESANN 2023 - [c4]Gaetano Saurio, Marco Muscas, Indro Spinelli, Valerio Rughetti, Irma Della Giovampaola, Simone Scardapane:
ArcheoWeedNet: Weed Classification in the Parco archeologico del Colosseo. ICIAP Workshops (1) 2023: 430-441 - [c3]Michele Guerra, Indro Spinelli, Simone Scardapane, Filippo Maria Bianchi:
Explainability in subgraphs-enhanced Graph Neural Networks. NLDL 2023 - [c2]Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane:
ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML 2023: 3-8 - [i11]Indro Spinelli, Riccardo Bianchini, Simone Scardapane:
Drop Edges and Adapt: a Fairness Enforcing Fine-tuning for Graph Neural Networks. CoRR abs/2302.11479 (2023) - [i10]Indro Spinelli, Michele Guerra, Filippo Maria Bianchi, Simone Scardapane:
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability. CoRR abs/2304.07152 (2023) - [i9]Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael M. Bronstein, Simone Scardapane, Paolo Di Lorenzo:
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module. CoRR abs/2305.16174 (2023) - [i8]Andrea Giuseppe Di Francesco, Giuliano Giampietro, Indro Spinelli, Danilo Comminiello:
GATSY: Graph Attention Network for Music Artist Similarity. CoRR abs/2311.00635 (2023) - 2022
- [j4]Indro Spinelli, Simone Scardapane, Amir Hussain, Aurelio Uncini:
FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning. IEEE Trans. Artif. Intell. 3(3): 344-354 (2022) - [i7]Michele Guerra, Indro Spinelli, Simone Scardapane, Filippo Maria Bianchi:
Explainability in subgraphs-enhanced Graph Neural Networks. CoRR abs/2209.07926 (2022) - 2021
- [j3]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Adaptive Propagation Graph Convolutional Network. IEEE Trans. Neural Networks Learn. Syst. 32(10): 4755-4760 (2021) - [j2]Simone Scardapane, Indro Spinelli, Paolo Di Lorenzo:
Distributed Training of Graph Convolutional Networks. IEEE Trans. Signal Inf. Process. over Networks 7: 87-100 (2021) - [i6]Indro Spinelli, Simone Scardapane, Amir Hussain, Aurelio Uncini:
Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning. CoRR abs/2104.14210 (2021) - [i5]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
A Meta-Learning Approach for Training Explainable Graph Neural Networks. CoRR abs/2109.09426 (2021) - 2020
- [j1]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Missing data imputation with adversarially-trained graph convolutional networks. Neural Networks 129: 249-260 (2020) - [i4]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Adaptive Propagation Graph Convolutional Network. CoRR abs/2002.10306 (2020) - [i3]Simone Scardapane, Indro Spinelli, Paolo Di Lorenzo:
Distributed Graph Convolutional Networks. CoRR abs/2007.06281 (2020)
2010 – 2019
- 2019
- [i2]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Missing Data Imputation with Adversarially-trained Graph Convolutional Networks. CoRR abs/1905.01907 (2019) - [i1]Indro Spinelli, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini:
Efficient data augmentation using graph imputation neural networks. CoRR abs/1906.08502 (2019) - 2017
- [c1]Indro Spinelli, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini:
Efficient Data Augmentation Using Graph Imputation Neural Networks. IIH-MSP (1) 2017: 57-66
Coauthor Index
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last updated on 2024-10-07 22:18 CEST by the dblp team
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