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Dive into the research topics where Mario Geiger is active.

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Featured researches published by Mario Geiger.


Proceedings of SPIE | 2012

Embedded microstructures for daylighting and seasonal thermal control

André Kostro; Mario Geiger; Nicolas Jolissaint; Marina A. González Lazo; Jean-Louis Scartezzini; Y. Leterrier; Andreas Schüler

A novel concept for an advanced fenestration system was studied and samples were produced to demonstrate the feasibility. The resulting novel glazing will combine the functions of daylighting, glare protection, and seasonal thermal control. Coated microstructures provide redirection of the incident solar radiation, thus simultaneously reducing glare and projecting daylight deep into the room in the same manner as an anidolic mirror-based system.The solar gains are reduced for chosen angles corresponding to a estival elevations of the sun, thereby minimising heating loads in winter and cooling loads in summer. A ray-tracing program developed especially for the study of laminar structures was used for the optimisation of structures with the above mentioned goals. The chosen solution is based on reflective surfaces embedded in a polymer film that can be combined with a standard doubled glazed window. The fabrication of such structures required several steps. The fabrication of a metallic mould with a relative high aspect ratio and mirror polished surfaces is followed by the production of an intermediate Polydimethylsiloxane moulds that was subsequently used to replicate the structure with a UV curable polymer. Selected facets of these samples were then coated with a thin film of highly reflective material in a physical vapour deposition process. Finally, the structures were filled with the same polymer to integrated the mirrors. The samples were characterised using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), confocal microscopy and laser profilometry. A miniature goniophotometer was built to assess the performance of the structured glazing. The daylighting behaviour was successfully demonstrated.


Applied Optics | 2016

CFSpro: ray tracing for design and optimization of complex fenestration systems using mixed dimensionality approach

André Kostro; Mario Geiger; Jean-Louis Scartezzini; Andreas Schüler

Advanced optical ray tracing software, CFSpro, was developed for the study and optimization of complex fenestration systems (CFSs). Using an algorithm mixing 2D and 3D approaches, accurate computation of large numbers of rays in extruded geometries can be performed and visualized in real time. A thin film model was included to assess the spectral control provided by coatings. In this paper, the ray tracing model is described and validated. A novel glazing, engineered with this simulation tool, is presented. It combines the functions of daylight provision, glare protection, and seasonal thermal control while conserving a view to the outside at near normal incidence.


Solar Energy | 2014

Thermal solar collector with VO2 absorber coating and V1-xWxO2 thermochromic glazing – Temperature matching and triggering

Antonio Paone; Mario Geiger; R. Sanjinés; Andreas Schüler


international conference on learning representations | 2018

Spherical CNNs

Taco S. Cohen; Mario Geiger; Jonas Moritz Kohler; Max Welling


arXiv: Learning | 2017

Convolutional Networks for Spherical Signals.

Taco S. Cohen; Mario Geiger; Jonas Moritz Kohler; Max Welling


arXiv: Learning | 2018

Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks).

Taco S. Cohen; Mario Geiger; Maurice Weiler


Proceedings of CISBAT 2011 - CleanTech for Sustainable Buildings | 2011

Towards microstructured glazing for daylighting and thermal control

André Kostro; Mario Geiger; Jean-Louis Scartezzini; Andreas Schueler


neural information processing systems | 2018

3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data

Maurice Weiler; Wouter Boomsma; Mario Geiger; Max Welling; Taco S. Cohen


arXiv: Learning | 2018

A jamming transition from under- to over-parametrization affects loss landscape and generalization

Stefano Spigler; Mario Geiger; Stéphane d'Ascoli; Levent Sagun; Giulio Biroli; Matthieu Wyart


arXiv: Disordered Systems and Neural Networks | 2018

The jamming transition as a paradigm to understand the loss landscape of deep neural networks.

Mario Geiger; Stefano Spigler; Stéphane d'Ascoli; Levent Sagun; Marco Baity-Jesi; Giulio Biroli; Matthieu Wyart

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André Kostro

École Polytechnique Fédérale de Lausanne

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Jean-Louis Scartezzini

École Polytechnique Fédérale de Lausanne

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Andreas Schüler

École Polytechnique Fédérale de Lausanne

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Andreas Schueler

École Polytechnique Fédérale de Lausanne

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Matthieu Wyart

École Polytechnique Fédérale de Lausanne

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Y. Leterrier

École Polytechnique Fédérale de Lausanne

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