Marcello Benedetti
- Artificial Intelligence top 1%
- Quantum Computing Algorithms and Architecture 19
- Quantum Information and Cryptography 11
- Neural Networks and Reservoir Computing 4
- Stochastic Gradient Optimization Techniques 2
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- Quantum and electron transport phenomena 2
- Quantum many-body systems 2
- Hardware and Architecture top 10%
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- Advancements in Semiconductor Devices and Circuit Design 3
- Advanced Memory and Neural Computing 2
- Co-authors
- Alejandro Perdomo‐OrtizJohn Realpe-GómezRupak BiswasEdward GrantÓscar PerdomoYunseong NamVicente Leyton‐OrtegaYuta Kikuchi
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsAtomic and Molecular Physics, and Optics
- Partner nations
- United KingdomUnited StatesColombia
In The Last Decade
Marcello Benedetti
18 papers receiving 895 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 875
- Computational Theory and Mathematics 179
- Atomic and Molecular Physics, and Optics 291
- Computational Mathematics 4
- Hardware and Architecture 33
Countries citing papers authored by Marcello Benedetti
This map shows the geographic impact of Marcello Benedetti's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marcello Benedetti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcello Benedetti more than expected).
Fields of papers citing papers by Marcello Benedetti
This network shows the impact of papers produced by Marcello Benedetti. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marcello Benedetti. The network helps show where Marcello Benedetti may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Marcello Benedetti, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 5 | |
| 4 | 2024 | 9 | |
| 5 | 2024 | 10 | |
| 6 | 2023 | 6 | |
| 7 | 2023 | 27 | |
| 8 | 2023 | 20 | |
| 9 | 2023 | 1 | |
| 10 | 2023 | 1 | |
| 11 | 2021 | 28 | |
| 12 | 2021 | 124 | |
| 13 | 2019 | 127 | |
| 14 | 2019 | 190 | |
| 15 | 2019 | 50 | |
| 16 | 2018 | 143 | |
| 17 | 2018 | 65 | |
| 18 | Quantum-assisted learning of graphical models with arbitrary pairwise connectivity | 2017 | 8 |
| 19 | 2016 | 138 | |
| 20 | Estimation of effective temperatures in quantum annealers for sampling applications: A case study towards deep learning | 2015 | 1 |
About Marcello Benedetti
Marcello Benedetti is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Atomic and Molecular Physics, and Optics, having authored 20 papers that have together received 955 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (19 papers), Quantum Information and Cryptography (11 papers), Neural Networks and Reservoir Computing (4 papers), Advancements in Semiconductor Devices and Circuit Design (3 papers), Advanced Memory and Neural Computing (2 papers), Stochastic Gradient Optimization Techniques (2 papers), Quantum and electron transport phenomena (2 papers) and Quantum many-body systems (2 papers). The work is most often cited by research in Artificial Intelligence (875 citations), Computational Theory and Mathematics (179 citations) and Atomic and Molecular Physics, and Optics (291 citations). Marcello Benedetti has collaborated with scholars based in United Kingdom, United States and Colombia. Frequent co-authors include Alejandro Perdomo‐Ortiz, John Realpe-Gómez, Rupak Biswas, Edward Grant, Óscar Perdomo, Yunseong Nam, Vicente Leyton‐Ortega, Yuta Kikuchi, Leonard Wossnig and Simone Severini. Their work appears in journals such as Scientific Reports, Nature Physics and Science Advances.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.