Publications

2020

• phiflow: A Differentiable PDE Solving Framework for Deep Learning via Physical Simulations
  
  • Holl Philipp
  • Koltun Vladlen
  • Um Kiwon
  • Thuerey Nils
  , 2020.
• « Je dois y aller ». Analyses de séquences de clôtures entre humains et robot
  
  • Licoppe Christian
  • Rollet Nicolas
  Réseaux : communication, technologie, société, Lavoisier, La Découverte, 2020, N°220-221 (2), pp.151. (10.3917/res.220.0151)
  DOI : 10.3917/res.220.0151
• Donsker's theorem in {Wasserstein}-1 distance
  
  • Coutin Laure
  • Decreusefond Laurent
  Electronic Communications in Probability, Institute of Mathematical Statistics (IMS), 2020, 25, pp.1--13. We compute the Wassertein-1 (or Kantorovitch-Rubinstein) distance between a random walk in $R^d$ and the Brownian motion. The proof is based on a new estimate of the Lipschitz modulus of the solution of the Stein's equation. As an application, we can evaluate the rate of convergence towards the local time at 0 of the Brownian motion. (10.1214/20-ECP308)
  DOI : 10.1214/20-ECP308
• D’un simple dessin de Léonard de Vinci aux "formes premières
  
  • Crettez Jean-Pierre
  ISTE Openscience, ISTE Ltd, 2020, 4 (4). (10.21494/ISTE.OP.2020.0557)
  DOI : 10.21494/ISTE.OP.2020.0557
• On linguistic descriptions of image content
  
  • Bloch Isabelle
  , 2020, pp.57-64.
• Tracking hundreds of people in densely crowded scenes with particle filtering supervising deep convolutional neural networks
  
  • Franchi G.
  • Aldea Emanuel
  • Dubuisson Séverine
  • Bloch Isabelle
  , 2020. (10.1109/ICIP40778.2020.9190953)
  DOI : 10.1109/ICIP40778.2020.9190953
• Change Detection Based on the Coefficient of Variation in SAR Time-Series of Urban Areas
  
  • Colin Koeniguer Elise
  • Nicolas Jean-Marie
  Remote Sensing, MDPI, 2020, 12 (13), pp.2089. This paper discusses change detection in SAR time-series. First, several statistical properties of the coefficient of variation highlight its pertinence for change detection. Subsequently, several criteria are proposed. The coefficient of variation is suggested to detect any kind of change. Furthermore, several criteria that are based on ratios of coefficients of variations are proposed to detect long events, such as construction test sites, or point-event, such as vehicles. These detection methods are first evaluated on theoretical statistical simulations to determine the scenarios where they can deliver the best results. The simulations demonstrate the greater sensitivity of the coefficient of variation to speckle mixtures, as in the case of agricultural plots. Conversely, they also demonstrate the greater specificity of the other criteria for the cases addressed: very short event or longer-term changes. Subsequently, detection performance is assessed on real data for different types of scenes and sensors (Sentinel-1, UAVSAR). In particular, a quantitative evaluation is performed with a comparison of our solutions with baseline methods. The proposed criteria achieve the best performance, with reduced computational complexity. On Sentinel-1 images containing mainly construction test sites, our best criterion reaches a probability of change detection of 90% for a false alarm rate that is equal to 5%. On UAVSAR images containing boats, the criteria proposed for short events achieve a probability of detection equal to 90% of all pixels belonging to the boats, for a false alarm rate that is equal to 2%. (10.3390/rs12132089)
  DOI : 10.3390/rs12132089
• Time Series Source Separation with Slow Flows
  
  • Pineau Edouard
  • Razakarivony Sébastien
  • Bonald Thomas
  , 2020. In this paper, we show that slow feature analysis (SFA), a common time series decomposition method, naturally fits into the flow-based models (FBM) framework, a type of invertible neural latent variable models. Building upon recent advances on blind source separation, we show that such a fit makes the time series decomposition identifiable.
• Real Time Multiscale Rendering of Dense Dynamic Stackings
  
  • Michel Elie
  • Boubekeur Tamy
  Computer Graphics Forum, Wiley, 2020, 39 (7), pp.169-179. Dense dynamic aggregates of similar elements are frequent in natural phenomena and challenging to render under full real time constraints. The optimal representation to render them changes drastically depending on the distance at which they are observed, ranging from sets of detailed textured meshes for near views to point clouds for distant ones. Our multiscale representation use impostors to achieve the mid-range transition from mesh-based to point-based scales. To ensure a visual continuum, the impostor model should match as closely as possible the mesh on one side, and reduce to a single pixel response that equals point rendering on the other. In this paper, we propose a model based on rich spherical impostors, able to combine precomputed as well as dynamic procedural data, and offering seamless transitions from close instanced meshes to distant points. Our approach is architectured around an on-the-fly discrimination mechanism and intensively exploits the rough spherical geometry of the impostor proxy. In particular, we propose a new sampling mechanism to reconstruct novel views from the precomputed ones, together with a new conservative occlusion culling method, coupled with a two-pass rendering pipeline leveraging early-Z rejection. As a result, our system scales well and is even able to render sand, while supporting completely dynamic stackings. (10.1111/cgf.14135)
  DOI : 10.1111/cgf.14135
• Estimated whole-brain and lobe-specific radiofrequency electromagnetic fields doses and brain volumes in preadolescents
  
  • Cabré-Riera Alba
  • El Marroun Hanan
  • Muetzel Ryan
  • van Wel Luuk
  • Liorni Ilaria
  • Thielens Arno
  • Birks Laura
  • Pierotti Livia
  • Huss Anke
  • Joseph Wout
  • Wiart Joe
  • Capstick Myles
  • Hillegers Manon
  • Vermeulen Roel
  • Cardis Elisabeth
  • Vrijheid Martine
  • White Tonya
  • Röösli Martin
  • Tiemeier Henning
  • Guxens Mònica
  Environment International, Elsevier, 2020. Objective: To assess the association between estimated whole-brain and lobe-specific radiofrequency electromagnetic fields (RF-EMF) doses, using an improved integrated RF-EMF exposure model, and brain volumes in preadolescents at 9-12 years old. Methods: Cross-sectional analysis in preadolescents aged 9-12 years from the Generation R Study, a population-based birth cohort set up in Rotterdam, The Netherlands (n = 2592). An integrated exposure model was used to estimate whole-brain and lobe-specific RF-EMF doses (mJ/kg/day) from different RF-EMF sources including mobile and Digital Enhanced Cordless Telecommunications (DECT) phone calls, other mobile phone uses than calling, tablet use, laptop use, and far-field sources. Whole-brain and lobe-specific RF-EMF doses were estimated for all RF-EMF sources together (i.e. overall) and for three groups of RF-EMF sources that lead to a different pattern of RF-EMF exposure. Information on brain volumes was extracted from magnetic resonance imaging scans. Results: Estimated overall whole-brain RF-EMF dose was 84.3 mJ/kg/day. The highest overall lobe-specific dose was estimated in the temporal lobe (307.1 mJ/kg/day). Whole-brain and lobe-specific RF-EMF doses from all RF-EMF sources together, from mobile and DECT phone calls, and from far-field sources were not associated with global, cortical, or subcortical brain volumes. However, a higher whole-brain RF-EMF dose from mobile phone use for internet browsing, e-mailing, and text messaging, tablet use, and laptop use while wirelessly connected to the internet was associated with a smaller caudate volume. Conclusions: Our results suggest that estimated whole-brain and lobe-specific RF-EMF doses were not related to brain volumes in preadolescents at 9-12 years old. Screen activities with mobile communication devices while https://doi. T wirelessly connected to the internet lead to low RF-EMF dose to the brain and our observed association may thus rather reflect effects of social or individual factors related to these specific uses of mobile communication devices. However, we cannot discard residual confounding, chance finding, or reverse causality. Further studies on mobile communication devices and their potential negative associations with brain development are warranted, regardless whether associations are due to RF-EMF exposure or to other factors related to their use. (10.1016/j.envint.2020.105808)
  DOI : 10.1016/j.envint.2020.105808
• Spectral Mesh Simplification
  
  • Lescoat Thibault
  • Liu Hsueh-Ti Derek -
  • Thiery Jean-Marc
  • Jacobson Alec
  • Boubekeur Tamy
  • Ovsjanikov Maks
  Computer Graphics Forum, Wiley, 2020. The spectrum of the Laplace-Beltrami operator is instrumental for a number of geometric modeling applications, from processing to analysis. Recently, multiple methods were developed to retrieve an approximation of a shape that preserves its eigenvectors as much as possible, but these techniques output a subset of input points with no connectivity, which limits their potential applications. Furthermore, the obtained Laplacian results from an optimization procedure, implying its storage alongside the selected points. Focusing on keeping a mesh instead of an operator would allow to retrieve the latter using the standard cotangent formulation, enabling easier processing afterwards. Instead, we propose to simplify the input mesh using a spectrum-preserving mesh decimation scheme, so that the Laplacian computed on the simplified mesh is spectrally close to the one of the input mesh. We illustrate the benefit of our approach for quickly approximating spectral distances and functional maps on low resolution proxies of potentially high resolution input meshes.
• Pythagore, J'adore
  
  • Zayana Karim
  Repères IREM, IREM, 2020. Ce texte reprend la trame d'un atelier proposé en avril-mai 2019 à Besançon pour le cinquantenaire des IREM, à Paris dans le cadre d'un plan national de formation, ainsi que dans les INSPÉ de Grenoble, Lyon et Nantes auprès des professeurs stagiaires (mathématiques et math-sciences). Il propose une étude, circonscrite aux programmes du second degré et à l'aune d'un questionnement QQOQCP 1 , de l'oeuvre de Pythagore. Flânons ainsi entre histoire, géographie, physique, musique, philosophie et bien sûr mathématiques... par Karim Zayana Inspecteur général, professeur invité à l'institut Mines-Télécom Avec esprit, humour et un zeste d'impertinence, on l'a mis en rap [1] et on l'a mis par terre [2] tandis qu'il nous mettait en pleurs [3]. En chanson, les artistes Isaaba, Renaud ou Aldebert, font rimer Pythagore sur nos chagrins d'école. Le grand homme ne sonne pourtant pas qu'avec « hardcore » et « mort »… À notre tour, dansons sur son trésor qui, charrié par les siècles, voyagea jusqu'à nous. L'exercice est plus sérieux qu'il y paraît, la simplicité d'un théorème, fût-il enfantin, n'est souvent qu'illusion. En savourer les mille et un reflets, en saisir l'essence, embrasser sa richesse reste un chemin ardu. La compréhension naît de l'effort, puis le plaisir de la compréhension. Là est la délivrance, point d'orgue culminant d'un processus long et sinueux qu'Heidegger résume en deux mots, chercher et questionner : « Tout questionner est un chercher. Tout chercher tire de ce qu'il recherche la direction qui précède et guide sa démarche. Questionner, c'est, sur le plan de la connaissance, chercher l'élément quant au fait qu'il soit et quant à son être tel. Chercher, sur le plan de la connaissance, s'appelle " recherche " quand est dégagé pour le déterminer ce après quoi la question se pose. » [4]. Toute la difficulté de trouver un sens aux choses est ici rendue par cette phrase, aussi complexe qu'abstraite. Il en va de même pour qui veut apprécier les mathématiques. Heureusement nous disposons d'outils. L'angle pédagogique des compétences en est un, et nous pourrions interroger en quoi la science des pythagoriciens les valide ou les développe, de calculer à communiquer en passant par modéliser sans oublier les facultés raisonner, représenter, chercher qu'il est d'usage d'effeuiller telles les pétales d'une fleur [5]. Une autre approche, que nous privilégions ici, relève de la méthodologie scientifique. Quand un chercheur analyse un problème, il le soumet un jour ou l'autre à ce crible [6] : 1. C'est de Qui, c'est Quand, c'est Où ? 1 Qui, Quand, Où, Quoi, Comment, Combien, Pour quoi/qui. Méthode empirique de questionnement circonstancié très utilisée en journalisme (de façon consciente), mais aussi en R&D (de façon sans doute moins formalisée).
• Private free-space communications based on chaos synchronization of mid-infrared quantum cascade laser light
  
  • Spitz O
  • Herdt A
  • Wu J
  • Wong C.-W
  • Elsässer W
  • Grillot F
  , 2020. Free Space Optics (FSO) is a growing technology offering higher bandwidth with fast and cost-effective deployment compared to fiber technology. This work demonstrates private free-space communication with quantum cascade lasers (QCLs). The secret message is encoded into a chaotic waveform so that the information is hard for an eavesdropper to extract [1]. Chaos-based transmissions in FSO are fundamentally restricted by atmospheric phenomena (e.g., turbulence, fog or scattering). Thus, the operating wavelength is a key parameter that has to be chosen wisely to reduce the impact of the environmental parameters. In this context, QCLs are relevant semiconductor lasers because their optical wavelength lies within mid-infrared domains where the atmosphere is highly transparent [2]. The simplest way to generate a chaotic optical carrier from a QCL is to feed back part of its emitted light into the device after a certain time delay [3], beyond which chaos synchronization between the drive and the response QCLs occurs.
• La théorie de l'information
  
  • Rioul Olivier
  , 2020, pp.7.
• Progressive Fusion for Unsupervised Binocular Depth Estimation using Cycled Networks
  
  • Pilzer Andrea
  • Lathuilière Stéphane
  • Xu Dan
  • Puscas Mihai Marian
  • Ricci Elisa
  • Sebe Nicu
  IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2020, 42 (10), pp.2380-2395. Recent deep monocular depth estimation approaches based on supervised regression have achieved remarkable performance. However, they require costly ground truth annotations during training. To cope with this issue, in this paper we present a novel unsupervised deep learning approach for predicting depth maps. We introduce a new network architecture, named Progressive Fusion Network (PFN), that is specifically designed for binocular stereo depth estimation. This network is based on a multi-scale refinement strategy that combines the information provided by both stereo views. In addition, we propose to stack twice this network in order to form a cycle. This cycle approach can be interpreted as a form of data-augmentation since, at training time, the network learns both from the training set images (in the forward half-cycle) but also from the synthesized images (in the backward half-cycle). The architecture is jointly trained with adversarial learning. Extensive experiments on the publicly available datasets KITTI, Cityscapes and ApolloScape demonstrate the effectiveness of the proposed model which is competitive with other unsupervised deep learning methods for depth prediction. (10.1109/TPAMI.2019.2942928)
  DOI : 10.1109/TPAMI.2019.2942928
• High resolution face age editing
  
  • Yao Xu
  • Newson Alasdair
  • Puy Gilles
  • Gousseau Yann
  • Hellier Pierre
  , 2020.
• On generalized hyper-bent functions
  
  • Mesnager Sihem
  Cryptography and Communications-Discrete Structures, Boolean Functions, and Sequences (CCDS), 2020.
• DNN Based Beam Selection in mmW Heterogeneous Networks
  
  • Jagyasi Deepa
  • Coupechoux Marceau
  , 2020. We consider a heterogeneous cellular network wherein multiple small cell millimeter wave (mmW) base stations (BSs) coexist with legacy sub-6GHz macro BSs. In the mmW band, small cells use multiple narrow beams to ensure sufficient coverage and User Equipments (UEs) have to select the best small cell and the best beam in order to access the network. This process usually based on exhaustive search may introduce unacceptable latency. In order to address this issue, we rely on the sub-6GHz macro BS support and propose a deep neural network (DNN) architecture that utilizes basic components from the Channel State Information (CSI) of sub-6GHz network as input features. The output of the DNN is the mmW BS and beam selection that can provide the best communication performance. In the set of features, we avoid using the UE location, which may not be readily available for every device. We formulate a mmW BS selection and beam selection problem as a classification and regression problem respectively and propose a joint solution using a branched neural network. The numerical comparison with the conventional exhaustive search results shows that the proposed design demonstrate better performance than exhaustive search in terms of la-tency with at least 85% accuracy.
• Codebooks from generalized bent Z4-valued quadratic forms
  
  • Qi Y.
  • Mesnager Sihem
  • Tang C.
  Discrete Mathematics, Elsevier, 2020.
• DYNAMIC-TDD INTERFERENCE TRACTABILITY APPROACHES AND PERFORMANCE ANALYSIS IN MACRO-CELL AND SMALL-CELL DEPLOYMENTS
  
  • Rachad J
  • Nasri R.
  • Decreusefond Laurent
  Annals of Telecommunications - annales des télécommunications, Springer, 2020. Meeting the continued growth in data traffic volume, Dynamic Time Division Duplex (D-TDD) has been introduced as a solution to deal with the uplink (UL) and downlink (DL) traffic asymmetry, mainly observed for dense heterogeneous network deployments, since it is based on instantaneous traffic estimation and provide more flexibility in resource assignment. However, the use of this feature requires new interference mitigation schemes capable to handle two additional types of interference between cells in opposite transmission direction: DL to UL and UL to DL interference. The aim of this work is to provide a complete analytical approach to model inter-cell interference in macro-cell and dense small-cell networks. We derive the explicit expressions of Interference to Signal Ratio (ISR) at each position of the network , in both DL and UL, to quantify the impact of each type of interference on the system performance. Also, we provide the explicit expressions of the coverage probability as functions of different system parameters by covering different scenarios. Finally, through system level simulations, we analyze the feasibility of D-TDD implementation in both deployments and we compare its performance to the static-TDD (S-TDD) configuration. (10.1007/s12243-020-00781-4)
  DOI : 10.1007/s12243-020-00781-4
• New characterizations and construction methods of bent and hyper-bent Boolean functions
  
  • Mesnager Sihem
  • Mandal B.
  • Tang C.
  Discrete Mathematics, Elsevier, 2020.
• KClist++: A Simple Algorithm for Finding k-Clique Densest Subgraphs in Large Graphs
  
  • Sun Bintao
  • Danisch Maximilien
  • Chan T-H Hubert
  • Sozio Mauro
  Proceedings of the VLDB Endowment (PVLDB), VLDB Endowment, 2020. The problem of finding densest subgraphs has received increasing attention in recent years finding applications in biology , finance, as well as social network analysis. The k-clique densest subgraph problem is a generalization of the densest subgraph problem, where the objective is to find a subgraph maximizing the ratio between the number of k-cliques in the subgraph and its number of nodes. It includes as a special case the problem of finding subgraphs with largest average number of triangles (k = 3), which plays an important role in social network analysis. Moreover, algorithms that deal with larger values of k can effectively find quasi-cliques. The densest subgraph problem can be solved in polynomial time with algorithms based on maximum flow, linear programming or a recent approach based on convex optimization. In particular, the latter approach can scale to graphs containing tens of billions of edges. While finding a densest subgraph in large graphs is no longer a bottleneck , the k-clique densest subgraph remains challenging even when k = 3. Our work aims at developing near-optimal and exact algorithms for the k-clique densest subgraph problem on large real-world graphs. We give a surprisingly simple procedure that can be employed to find the maximal k-clique densest subgraph in large-real world graphs. By leveraging appealing properties of existing results, we combine it with a recent approach for listing all k-cliques in a graph and a sampling scheme, obtaining the state-of-the-art approaches for the aforementioned problem. Our theoretical results are complemented with an extensive experimental evaluation showing the effectiveness of our approach in large real-world graphs.
• SENSITIVITY ANALYSIS FOR STOCHASTIC SIMULATORS USING DIFFERENTIAL ENTROPY
  
  • Azzi Soumaya
  • Sudret Bruno
  • Wiart Joe
  International Journal for Uncertainty Quantification, Begell House Publishers, 2020, 10 (1), pp.25-33. (10.1615/Int.J.UncertaintyQuantification.2020031610)
  DOI : 10.1615/Int.J.UncertaintyQuantification.2020031610
• Solving $x^{2^k+1}+x+a=0$ in $\mathbb{F}_{2^n}$ with $\gcd(n,k)=1$
  
  • Kim K. H.
  • Mesnager Sihem
  Finite Fields and Their Applications, Elsevier, 2020.
• Several classes of minimal linear codes with few weights from weakly regular plateaued function
  
  • Mesnager Sihem
  • Sinak A.
  IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2020.