Timothée Lesort

1.1k total citations · 1 hit paper
7 papers, 459 citations indexed

About

Timothée Lesort is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Infectious Diseases. According to data from OpenAlex, Timothée Lesort has authored 7 papers receiving a total of 459 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Infectious Diseases. Recurrent topics in Timothée Lesort's work include Domain Adaptation and Few-Shot Learning (5 papers), Reinforcement Learning in Robotics (2 papers) and ECG Monitoring and Analysis (1 paper). Timothée Lesort is often cited by papers focused on Domain Adaptation and Few-Shot Learning (5 papers), Reinforcement Learning in Robotics (2 papers) and ECG Monitoring and Analysis (1 paper). Timothée Lesort collaborates with scholars based in France, Australia and Canada. Timothée Lesort's co-authors include David Filliat, Natalia Díaz-Rodríguez, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, Jocelyn Faubert, Mohammad Sajjad Ghaemi, Irina Rish, Xinrui Li and Florian Bordes and has published in prestigious journals such as Neural Networks, Computers in Biology and Medicine and HAL (Le Centre pour la Communication Scientifique Directe).

In The Last Decade

Timothée Lesort

7 papers receiving 447 citations

Hit Papers

align trajectories

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.

Continual Learning for Robotics: Definition, Framework, Learning\n Strategies, Opportunities and Challenges

2019 288 citations Timothée Lesort, Vincenzo Lomonaco et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Timothée Lesort France	5	313	136	76	41	36	7	459
Pitoyo Hartono Japan	10	183 0.6×	106 0.8×	63 0.8×	27 0.7×	12 0.3×	74	393
Ronghua Luo China	9	187 0.6×	136 1.0×	79 1.0×	20 0.5×	27 0.8×	32	361
Francisco Cruz Australia	11	247 0.8×	62 0.5×	108 1.4×	36 0.9×	11 0.3×	32	376
Mark Palatucci United States	5	349 1.1×	216 1.6×	42 0.6×	104 2.5×	15 0.4×	7	573
Aleksandar Jevtić Spain	13	127 0.4×	155 1.1×	119 1.6×	29 0.7×	25 0.7×	36	450
Amr El-Desoky Mousa Germany	13	412 1.3×	125 0.9×	30 0.4×	21 0.5×	33 0.9×	25	588
Mathias Lechner Austria	9	202 0.6×	56 0.4×	87 1.1×	70 1.7×	97 2.7×	22	458
Alexander Gepperth Germany	11	205 0.7×	191 1.4×	31 0.4×	28 0.7×	27 0.8×	46	415
Carmen Bisogni Italy	15	166 0.5×	389 2.9×	18 0.2×	22 0.5×	20 0.6×	40	629
Zhenyu Yan Hong Kong	11	141 0.5×	114 0.8×	23 0.3×	15 0.4×	66 1.8×	41	363

Countries citing papers authored by Timothée Lesort

Since Specialization

Citations

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

Fields of papers citing papers by Timothée Lesort

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Timothée Lesort

This figure shows the co-authorship network connecting the top 25 collaborators of Timothée Lesort. A scholar is included among the top collaborators of Timothée Lesort 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 Timothée Lesort. Timothée Lesort is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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7 of 7 papers shown

1.

Ghaemi, Mohammad Sajjad, et al.. (2023). Amplifying pathological detection in EEG signaling pathways through cross-dataset transfer learning. Computers in Biology and Medicine. 169. 107893–107893. 9 indexed citations

2.

Gepperth, Alexander, et al.. (2022). Beyond Supervised Continual Learning: a Review. arXiv (Cornell University). 1 indexed citations

3.

Lesort, Timothée, Vincenzo Lomonaco, Andrei Stoian, et al.. (2019). Continual Learning for Robotics: Definition, Framework, Learning\n Strategies, Opportunities and Challenges. arXiv (Cornell University). 288 indexed citations breakdown →

4.

Lesort, Timothée, Vincenzo Lomonaco, Andrei Stoian, et al.. (2019). Continual Learning for Robotics. arXiv (Cornell University). 10 indexed citations

5.

Lesort, Timothée, et al.. (2019). Deep unsupervised state representation learning with robotic priors: a robustness analysis. HAL (Le Centre pour la Communication Scientifique Directe). 1–8. 5 indexed citations

6.

Lesort, Timothée, et al.. (2018). State representation learning for control: An overview. Neural Networks. 108. 379–392. 145 indexed citations

7.

Lesort, Timothée, et al.. (2018). Evaluation of generative networks through their data augmentation capacity. 1 indexed citations

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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