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  1. Book ; Online: Neurolaw: The Call for Adjusting Theory Based on Scientific Results

    Muñoz, José M. / Muñoz, José M. / García-López, Eric / Rusconi, Elena

    2020  

    Keywords Science: general issues ; Psychology ; neurolaw ; free will ; criminal responsibility ; psychopathy ; neuroprediction ; adolescent brain ; addiction ; decision neuroscience
    Size 1 electronic resource (149 pages)
    Publisher Frontiers Media SA
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT021231597
    ISBN 9782889662081 ; 288966208X
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article ; Online: Achieving cognitive liberty

    Muñoz, José M

    Science (New York, N.Y.)

    2023  Volume 379, Issue 6637, Page(s) 1097

    Abstract: Neurotechnologies necessitate new thinking on human rights. ...

    Abstract Neurotechnologies necessitate new thinking on human rights.
    Language English
    Publishing date 2023-03-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 128410-1
    ISSN 1095-9203 ; 0036-8075
    ISSN (online) 1095-9203
    ISSN 0036-8075
    DOI 10.1126/science.adf8306
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Equal access to mental augmentation: Should it be a fundamental right?

    Muñoz, José M / Borbón, Diego

    Brain stimulation

    2023  Volume 16, Issue 4, Page(s) 1094–1096

    Language English
    Publishing date 2023-06-01
    Publishing country United States
    Document type Letter
    ZDB-ID 2394410-9
    ISSN 1876-4754 ; 1935-861X
    ISSN (online) 1876-4754
    ISSN 1935-861X
    DOI 10.1016/j.brs.2023.05.003
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Zooming Out from the Brain to Foster Translational Neuroethics.

    Muñoz, José M / Bernácer, Javier

    AJOB neuroscience

    2023  Volume 14, Issue 4, Page(s) 405–407

    Language English
    Publishing date 2023-10-19
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 2576262-X
    ISSN 2150-7759 ; 2150-7740
    ISSN (online) 2150-7759
    ISSN 2150-7740
    DOI 10.1080/21507740.2023.2257167
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Chile - right to free will needs definition.

    Muñoz, José M

    Nature

    2019  Volume 574, Issue 7780, Page(s) 634

    Language English
    Publishing date 2019-10-29
    Publishing country England
    Document type Letter
    ZDB-ID 120714-3
    ISSN 1476-4687 ; 0028-0836
    ISSN (online) 1476-4687
    ISSN 0028-0836
    DOI 10.1038/d41586-019-03295-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Somatic Markers, Rhetoric, and Post-truth.

    Muñoz, José M

    Frontiers in psychology

    2017  Volume 8, Page(s) 1273

    Language English
    Publishing date 2017-07-26
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2563826-9
    ISSN 1664-1078
    ISSN 1664-1078
    DOI 10.3389/fpsyg.2017.01273
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: Editorial: Neurorights and Mental Freedom: Emerging Challenges to Debates on Human Dignity and Neurotechnologies.

    García-López, Eric / Muñoz, José M / Andorno, Roberto

    Frontiers in human neuroscience

    2021  Volume 15, Page(s) 823570

    Language English
    Publishing date 2021-12-22
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2425477-0
    ISSN 1662-5161
    ISSN 1662-5161
    DOI 10.3389/fnhum.2021.823570
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Book ; Online: Retrieval of Boost Invariant Symbolic Observables via Feature Importance

    Munoz, Jose M / Batatia, Ilyes / Ortner, Christoph / Romeo, Francesco

    2023  

    Abstract: Deep learning approaches for jet tagging in high-energy physics are characterized as black boxes that process a large amount of information from which it is difficult to extract key distinctive observables. In this proceeding, we present an alternative ... ...

    Abstract Deep learning approaches for jet tagging in high-energy physics are characterized as black boxes that process a large amount of information from which it is difficult to extract key distinctive observables. In this proceeding, we present an alternative to deep learning approaches, Boost Invariant Polynomials, which enables direct analysis of simple analytic expressions representing the most important features in a given task. Further, we show how this approach provides an extremely low dimensional classifier with a minimum set of features representing %effective discriminating physically relevant observables and how it consequently speeds up the algorithm execution, with relatively close performance to the algorithm using the full information.
    Keywords Physics - Computational Physics ; Computer Science - Machine Learning ; High Energy Physics - Experiment
    Publishing date 2023-06-23
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Book ; Online: BIP

    Munoz, Jose M / Batatia, Ilyes / Ortner, Christoph

    Boost Invariant Polynomials for Efficient Jet Tagging

    2022  

    Abstract: Deep Learning approaches are becoming the go-to methods for data analysis in High Energy Physics (HEP). Nonetheless, most physics-inspired modern architectures are computationally inefficient and lack interpretability. This is especially the case with ... ...

    Abstract Deep Learning approaches are becoming the go-to methods for data analysis in High Energy Physics (HEP). Nonetheless, most physics-inspired modern architectures are computationally inefficient and lack interpretability. This is especially the case with jet tagging algorithms, where computational efficiency is crucial considering the large amounts of data produced by modern particle detectors. In this work, we present a novel, versatile and transparent framework for jet representation; invariant to Lorentz group boosts, which achieves high accuracy on jet tagging benchmarks while being orders of magnitudes faster to train and evaluate than other modern approaches for both supervised and unsupervised schemes.
    Keywords Physics - Computational Physics ; Computer Science - Machine Learning ; High Energy Physics - Experiment
    Publishing date 2022-07-17
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article: Editorial: Neurolaw: The Call for Adjusting Theory Based on Scientific Results.

    Muñoz, José M / García-López, Eric / Rusconi, Elena

    Frontiers in psychology

    2020  Volume 11, Page(s) 582302

    Language English
    Publishing date 2020-10-09
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2563826-9
    ISSN 1664-1078
    ISSN 1664-1078
    DOI 10.3389/fpsyg.2020.582302
    Database MEDical Literature Analysis and Retrieval System OnLINE

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