Recurrent Deep Neural Networks for Nucleosome Classification. - Domenico Amato; Mattia Antonino Di Gangi; Giosuè Lo Bosco; Riccardo Rizzo (CIBB, 2018)

CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification. - Domenico Amato; Giosuè Lo Bosco; Riccardo Rizzo (BMC Bioinform., 2020)

Learning from Data to Speed-up Sorted Table Search Procedures: Methodology and Practical Guidelines. - Domenico Amato; Giosuè Lo Bosco; Raffaele Giancarlo (CoRR, 2020)

Learned Sorted Table Search and Static Indexes in Small Model Space. - Domenico Amato; Giosuè Lo Bosco; Raffaele Giancarlo (AI*IA, 2021)

Learned Sorted Table Search and Static Indexes in Small Space: Methodological and Practical Insights via an Experimental Study. - Domenico Amato; Raffaele Giancarlo; Giosuè Lo Bosco (CoRR, 2021)

On the Suitability of Neural Networks as Building Blocks for the Design of Efficient Learned Indexes. - Domenico Amato; Giosuè Lo Bosco; Raffaele Giancarlo (EANN, 2022)

Standard Vs Uniform Binary Search and Their Variants in Learned Static Indexing: The Case of the Searching on Sorted Data Benchmarking Software Platform. - Domenico Amato; Giosuè Lo Bosco; Raffaele Giancarlo (CoRR, 2022)

A Tour of Learned Static Sorted Sets Dictionaries: From Specific to Generic with an Experimental Performance Analysis. - Domenico Amato (2022)

Transformers for Interpretable Classification of Histopathological Images. - Domenico Amato; Salvatore Calderaro; Giosuè Lo Bosco; Giuseppe Marino; Filippo Vella; Riccardo Rizzo (CIBB, 2023)

From Specific to Generic Learned Sorted Set Dictionaries: A Theoretically Sound Paradigm Yelding Competitive Data Structural Boosters in Practice. - Domenico Amato; Giosuè Lo Bosco; Raffaele Giancarlo (CoRR, 2023)

Standard versus uniform binary search and their variants in learned static indexing: The case of the searching on sorted data benchmarking software platform. - Domenico Amato; Giosuè Lo Bosco; Raffaele Giancarlo (Softw. Pract. Exp., 2023)

Learned Sorted Table Search and Static Indexes in Small-Space Data Models. - Domenico Amato; Raffaele Giancarlo; Giosuè Lo Bosco (Data, 2023)

Metric Learning in Histopathological Image Classification: Opening the Black Box. - Domenico Amato; Salvatore Calderaro; Giosuè Lo Bosco; Riccardo Rizzo; Filippo Vella (Sensors, 2023)

Neural networks as building blocks for the design of efficient learned indexes. - Domenico Amato; Giosuè Lo Bosco; Raffaele Giancarlo (Neural Comput. Appl., 2023)

Proteins Transcription Factor Prediction Using Graph Neural Networks. - Domenico Amato; Salvatore Calderaro; Giosuè Lo Bosco; Filippo Vella; Riccardo Rizzo (CIBB, 2024)

Bacteria Taxonomic Classification using Graph Neural Networks. - Domenico Amato; Salvatore Calderaro; Giosuè Lo Bosco; Riccardo Rizzo; Filippo Vella (EAIS, 2024)

The GECo algorithm for Graph Neural Networks Explanation. - Salvatore Calderaro; Domenico Amato; Giosuè Lo Bosco; Riccardo Rizzo; Filippo Vella (CoRR, 2024)

Correction to: Neural networks as building blocks for the design of efficient learned indexes. - Domenico Amato; Giosuè Lo Bosco; Raffaele Giancarlo (Neural Comput. Appl., 2024)

Explainable Histopathology Image Classification with Self-organizing Maps: A Granular Computing Perspective. - Domenico Amato; Salvatore Calderaro; Giosuè Lo Bosco; Riccardo Rizzo; Filippo Vella (Cogn. Comput., 2024)