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On theories of everything : are physicists actually 'lost in math'?

Authors : Parrochia, Daniel;

Subjects: Theories of everything; String Theory; GUTs

Source: https://hal.science/hal-03286062 ; 2021.

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Former les prochains spécialistes de l'information à la désinformation

Authors : Tranchand-Granger, Laurence;

Subjects: [CHIM]Chemical Sciences; [INFO]Computer Science [cs]; [MATH]Mathematics [math]Mulhouse; France

Source: Congrès National de la Recherche des IUT ; https://hal.science/hal-04619831 ; Congrès National de la Recherche des IUT, Université de Haute-Alsace (UHA) Mulhouse - Colmar [Université de

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L'APC (approche par compétences): une perspective historique

Authors : Goutagny, Sarah;

Subjects: [CHIM]Chemical Sciences; [INFO]Computer Science [cs]; [MATH]Mathematics [math]Mulhouse; France

Source: Congrès National de la Recherche des IUT ; https://hal.science/hal-04619832 ; Congrès National de la Recherche des IUT, Université de Haute-Alsace (UHA) Mulhouse - Colmar [Université de

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Combinatoric, mimetic and non mimetic aspects of creativity

Authors : Parrochia, Daniel;

Subjects: Creativity in nature inventive stimulation combinatorics Lull mathematical creativity Ramanujan Grothendieck; Creativity in nature; inventive stimulation

Source: https://hal.science/hal-04524062 ; 2024.

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Hegel, Erdös-Anning theorem and the Pythagorean triangle ; Hegel, le théorème de Erdös-Anning et le triangle pythagoricien ; Hegel, Erdös-Anning theorem and the Pythagorean triangle: Hegel, as we know, took as an emblem of mathematical thought the Pythagorean theorem, whose (Euclidean) demonstration seemed to him to illustrate what he rejected, namely a thought of understanding, dismembering reality instead of progressing dialectically towards synthesis. In this article, we show that Hegelian triplicity in its circular finitude results from an impossibility. A mathematical theorem, the Erd\'{o}s-Anning theorem shows that points located at integer distances can only be aligned and in infinite number. If we identify concepts with discrete points, and if we want to remain in the finite, it is clear that they must be non-aligned. Therefore, their circular arrangement on a unit circle is a solution, which can still be generalized on the sphere. But this proves, contrary to Hegel's assertions, that the concepts themselves can be decomposed in a recto-triangular manner.

Authors : Parrochia, Daniel;

Subjects: Hegel Erdös-Anning theorem Pythagorean triples discrete geometry; Hegel; Erdös-Anning theorem

Source: https://hal.science/hal-04648925 ; 2024.

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Academic Journal

Predicting missing Energy Performance Certificates: Spatial interpolation of mixture distributions ; Prédire les DPE manquants : Interpolation spatiale de distributions de mélanges

Authors : Grossouvre, Marc; Rullière, Didier; Villot, Jonathan ...

Subjects: Climate governance; Energy efficiency; Multi-scale processes

Source: ISSN: 2666-5468 ; Energy and IA ; https://hal.science/hal-03276127 ; Energy and IA, In press, 16, pp.100339. ⟨10.1016/j.egyai.2024.100339⟩.

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Coordinate Descent for SLOPE

Authors : Larsson, Johan; Klopfenstein, Quentin; Massias, Mathurin ...

Subjects: [MATH]Mathematics [math]Valencia; Spain

Source: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics ; 26th International Conference on Artificial Intelligence and Statistics - AISTATS 2023 ;

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Does a sparse ReLU network training problem always admit an optimum?

Authors : Le, Quoc-Tung; Riccietti, Elisa; Gribonval, Rémi ...

Subjects: Topology; Best Approximation Property; Sparse ReLU Neural NetworkNew Orleans (Lousiane); United States

Source: Thirty-seventh Conference on Neural Information Processing Systems ; https://inria.hal.science/hal-04108849 ; Thirty-seventh Conference on Neural Information Processing Systems, Dec 2023, New Orleans

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Does a sparse ReLU network training problem always admit an optimum?

Authors : Le, Quoc-Tung; Riccietti, Elisa; Gribonval, Rémi ...

Subjects: Topology; Best Approximation Property; Sparse ReLU Neural NetworkNew Orleans (Lousiane); United States

Source: NeurIPS 2023 - Thirty-seventh Conference on Neural Information Processing Systems ; https://inria.hal.science/hal-04108849 ; NeurIPS 2023 - Thirty-seventh Conference on Neural Information Processing

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