Leonard Wossnig

2.1k total citations · 1 hit paper
15 papers, 1.2k citations indexed

About

Leonard Wossnig is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Molecular Biology. According to data from OpenAlex, Leonard Wossnig has authored 15 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 3 papers in Atomic and Molecular Physics, and Optics and 1 paper in Molecular Biology. Recurrent topics in Leonard Wossnig's work include Quantum Computing Algorithms and Architecture (12 papers), Quantum Information and Cryptography (10 papers) and Neural Networks and Reservoir Computing (3 papers). Leonard Wossnig is often cited by papers focused on Quantum Computing Algorithms and Architecture (12 papers), Quantum Information and Cryptography (10 papers) and Neural Networks and Reservoir Computing (3 papers). Leonard Wossnig collaborates with scholars based in United Kingdom, United States and China. Leonard Wossnig's co-authors include Edward Grant, Hongxiang Chen, Simone Severini, Jules Tilly, Shuxiang Cao, Kanav Setia, Ying Li, Ivan Rungger, George H. Booth and Jonathan Tennyson and has published in prestigious journals such as Physical Review Letters, Physics Reports and Drug Discovery Today.

In The Last Decade

Leonard Wossnig

15 papers receiving 1.1k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The Variational Quantum Eigensolver: A review of methods and best practices

2022 552 citations Jules Tilly, Hongxiang Chen et al. Physics Reports profile →

Peers

Countries citing papers authored by Leonard Wossnig

Since Specialization

Citations

This map shows the geographic impact of Leonard Wossnig'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 Leonard Wossnig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leonard Wossnig more than expected).

Fields of papers citing papers by Leonard Wossnig

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leonard Wossnig. 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 Leonard Wossnig. The network helps show where Leonard Wossnig may publish in the future.

Co-authorship network of co-authors of Leonard Wossnig

This figure shows the co-authorship network connecting the top 25 collaborators of Leonard Wossnig. A scholar is included among the top collaborators of Leonard Wossnig based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Leonard Wossnig. Leonard Wossnig is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	Best practices for machine learning in antibody discovery and development 2024 ·Drug Discovery Today ·Leonard Wossnig, Norbert Furtmann, Andrew Buchanan, Sandeep Kumar, Victor Greiff	9
2	The Variational Quantum Eigensolver: A review of methods and best practices breakdown → 2022 ·Physics Reports ·Jules Tilly, Hongxiang Chen, Shuxiang Cao, (unknown), Kanav Setia, Ying Li, Edward Grant, Leonard Wossnig, Ivan Rungger, George H. Booth, Jonathan Tennyson	552
3	Intelligent drug discovery 2021 ·Physics World ·Leonard Wossnig	1
4	The Variational Quantum Eigensolver: a review of methods and best practices 2021 ·arXiv (Cornell University) ·Jules Tilly, Hongxiang Chen, Shuxiang Cao, (unknown), Kanav Setia, Ying Li, Edward R. Grant, Leonard Wossnig, Ivan Rungger, George H. Booth, Jonathan Tennyson	6
5	Computation of molecular excited states on IBM quantum computers using a discriminative variational quantum eigensolver 2020 ·Physical review. A ·Jules Tilly, Glenn Jones, Hongxiang Chen, Leonard Wossnig, Edward Grant	23
6	A quantum algorithm for simulating non-sparse Hamiltonians 2020 ·Quantum Information and Computation ·Chunhao Wang, Leonard Wossnig	9
7	Cost-function embedding and dataset encoding for machine learning with parametrized quantum circuits 2020 ·Physical review. A ·Shuxiang Cao, Leonard Wossnig, Brian Vlastakis, Peter Leek, Edward Grant	19
8	Statistical limits of supervised quantum learning 2020 ·Physical review. A ·Carlo Ciliberto, Andrea Rocchetto, Alessandro Rudi, Leonard Wossnig	5
9	Universal discriminative quantum neural networks 2020 ·Quantum Machine Intelligence ·Hongxiang Chen, Leonard Wossnig, Simone Severini, Hartmut Neven, Morteza Mohseni	52
10	Quantum machine learning: Challenges and Opportunities 2019 ·Bulletin of the American Physical Society ·Leonard Wossnig, Simone Severini	1
11	Adversarial quantum circuit learning for pure state approximation 2019 ·New Journal of Physics ·Marcello Benedetti, Edward Grant, Leonard Wossnig, Simone Severini	50
12	Cost function embedding and dataset encoding for machine learning with parameterized quantum circuits 2019 ·arXiv (Cornell University) ·Shuxiang Cao, Leonard Wossnig, Brian Vlastakis, Peter Leek, Edward Grant	1
13	Quantum Linear System Algorithm for Dense Matrices 2018 ·Physical Review Letters ·Leonard Wossnig, Zhikuan Zhao, Anupam Prakash	143
14	Quantum machine learning: a classical perspective 2018 ·Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences ·Carlo Ciliberto, Mark Herbster, (unknown), Massimiliano Pontil, Andrea Rocchetto, Simone Severini, Leonard Wossnig	279
15	The Role of Information in Group Formation 2016 ·(unknown), Leonard Wossnig, Johannes Thiele	1

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.

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