Davide Zambrano

About Davide Zambrano

Davide Zambrano, With an exceptional h-index of 13 and a recent h-index of 10 (since 2020), a distinguished researcher at École Polytechnique Fédérale de Lausanne, specializes in the field of Deep Learning, Computer Vision, Spiking Neural Networks, Reinforcement Learning, Sport Analytics.

His recent articles reflect a diverse array of research interests and contributions to the field:

DeepSportradar-v2: A Multi-Sport Computer Vision Dataset for Sport Understandings

Vipriors 3: Visual inductive priors for data-efficient deep learning challenges

Leveraging spiking deep neural networks to understand the neural mechanisms underlying selective attention

Vipriors 2: visual inductive priors for data-efficient deep learning challenges

DeepSportradar-v1: Computer vision dataset for sports understanding with high quality annotations

Autonomous detection and deterrence of pigeons on buildings by drones

Learning continuous-time working memory tasks with on-policy neural reinforcement learning

Seeking quality diversity in evolutionary co-design of morphology and control of soft tensegrity modular robots

Davide Zambrano Information

University

Position

(EPFL)

Citations(all)

407

Citations(since 2020)

284

Cited By

200

hIndex(all)

13

hIndex(since 2020)

10

i10Index(all)

14

i10Index(since 2020)

10

Email

University Profile Page

Google Scholar

Davide Zambrano Skills & Research Interests

Deep Learning

Computer Vision

Spiking Neural Networks

Reinforcement Learning

Sport Analytics

Top articles of Davide Zambrano

Title

Journal

Author(s)

Publication Date

DeepSportradar-v2: A Multi-Sport Computer Vision Dataset for Sport Understandings

Maxime Istasse

Vladimir Somers

Pratheeban Elancheliyan

Jaydeep De

Davide Zambrano

2023/10/29

Vipriors 3: Visual inductive priors for data-efficient deep learning challenges

arXiv preprint arXiv:2305.19688

Robert-Jan Bruintjes

Attila Lengyel

Marcos Baptista Rios

Osman Semih Kayhan

Davide Zambrano

...

2023/5/31

Leveraging spiking deep neural networks to understand the neural mechanisms underlying selective attention

Journal of Cognitive Neuroscience

Lynn KA Sörensen

Davide Zambrano

Heleen A Slagter

Sander M Bohté

H Steven Scholte

2022/1/20

Vipriors 2: visual inductive priors for data-efficient deep learning challenges

arXiv preprint arXiv:2201.08625

Attila Lengyel

Robert-Jan Bruintjes

Marcos Baptista Rios

Osman Semih Kayhan

Davide Zambrano

...

2022/1/21

DeepSportradar-v1: Computer vision dataset for sports understanding with high quality annotations

Gabriel Van Zandycke

Vladimir Somers

Maxime Istasse

Carlo Del Don

Davide Zambrano

2022/10/14

Autonomous detection and deterrence of pigeons on buildings by drones

IEEE Access

Fabrizio Schiano

Dominik Natter

Davide Zambrano

Dario Floreano

2021/12/20

Learning continuous-time working memory tasks with on-policy neural reinforcement learning

Neurocomputing

Davide Zambrano

Pieter R Roelfsema

Sander Bohte

2021/10/21

Seeking quality diversity in evolutionary co-design of morphology and control of soft tensegrity modular robots

Enrico Zardini

Davide Zappetti

Davide Zambrano

Giovanni Iacca

Dario Floreano

2021/6/26

See List of Professors in Davide Zambrano University(École Polytechnique Fédérale de Lausanne)

Co-Authors

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