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2020 – today
- 2024
[j7]Domenico Amato, Salvatore Calderaro
, Giosuè Lo Bosco, Riccardo Rizzo, Filippo Vella:
Explainable Histopathology Image Classification with Self-organizing Maps: A Granular Computing Perspective. Cogn. Comput. 16(6): 2999-3019 (2024)- [j6]Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo:
Correction to: Neural networks as building blocks for the design of efficient learned indexes. Neural Comput. Appl. 36(2): 1047 (2024) - [c4]Domenico Amato, Salvatore Calderaro, Giosuè Lo Bosco, Riccardo Rizzo, Filippo Vella:
Bacteria Taxonomic Classification using Graph Neural Networks. EAIS 2024: 1-6 - [i6]Salvatore Calderaro, Domenico Amato, Giosuè Lo Bosco, Riccardo Rizzo, Filippo Vella:
The GECo algorithm for Graph Neural Networks Explanation. CoRR abs/2411.11391 (2024) - 2023
- [j5]Domenico Amato, Raffaele Giancarlo, Giosuè Lo Bosco:
Learned Sorted Table Search and Static Indexes in Small-Space Data Models. Data 8(3): 56 (2023) - [j4]Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo:
Neural networks as building blocks for the design of efficient learned indexes. Neural Comput. Appl. 35(29): 21399-21414 (2023) - [j3]Domenico Amato, Salvatore Calderaro, Giosuè Lo Bosco, Riccardo Rizzo, Filippo Vella:
Metric Learning in Histopathological Image Classification: Opening the Black Box. Sensors 23(13): 6003 (2023) - [j2]Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo:
Standard versus uniform binary search and their variants in learned static indexing: The case of the searching on sorted data benchmarking software platform. Softw. Pract. Exp. 53(2): 318-346 (2023) - [i5]Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo:
From Specific to Generic Learned Sorted Set Dictionaries: A Theoretically Sound Paradigm Yelding Competitive Data Structural Boosters in Practice. CoRR abs/2309.00946 (2023) - 2022
- [c3]Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo:
On the Suitability of Neural Networks as Building Blocks for the Design of Efficient Learned Indexes. EANN 2022: 115-127 - [i4]Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo:
Standard Vs Uniform Binary Search and Their Variants in Learned Static Indexing: The Case of the Searching on Sorted Data Benchmarking Software Platform. CoRR abs/2201.01554 (2022) - [i3]Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo:
On the Suitability of Neural Networks as Building Blocks for The Design of Efficient Learned Indexes. CoRR abs/2203.14777 (2022) - 2021
- [c2]Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo:
Learned Sorted Table Search and Static Indexes in Small Model Space. AI*IA 2021: 462-477 - [i2]Domenico Amato, Raffaele Giancarlo, Giosuè Lo Bosco:
Learned Sorted Table Search and Static Indexes in Small Space: Methodological and Practical Insights via an Experimental Study. CoRR abs/2107.09480 (2021) - 2020
- [j1]Domenico Amato, Giosuè Lo Bosco, Riccardo Rizzo:
CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification. BMC Bioinform. 21-S(8): 326 (2020) - [i1]Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo:
Learning from Data to Speed-up Sorted Table Search Procedures: Methodology and Practical Guidelines. CoRR abs/2007.10237 (2020)
2010 – 2019
- 2018
- [c1]Domenico Amato, Mattia Antonino Di Gangi, Giosuè Lo Bosco, Riccardo Rizzo:
Recurrent Deep Neural Networks for Nucleosome Classification. CIBB 2018: 118-127
Coauthor Index
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