Variational Latent Discrete Representation for Time Series Modelling

Discrete latent space models have recently achieved performance on par with their continuous counterparts in deep variational inference. While they still face various implementation challenges, these models offer the opportunity for a better interpretation of latent spaces, as well as a more direct representation of naturally discrete phenomena. Most recent approaches propose to train separately very high-dimensional prior models on the discrete latent data which is a challenging task on its own. In this paper, we introduce a latent data model where the discrete state is a Markov chain, which allows fast end-to-end training. The performance of our generative model is assessed on a building management dataset and on the publicly available Electricity Transformer Dataset

Importance of the dynamics of adsorption and of a transient interfacial stress on the formation of aggregates of IgG antibodies

International audienceIt is common knowledge that aggregation of proteins may occur in aqueous solutions under mechanical stress (shaking or high shear), even in solutions that are stable at rest. Addition of surfactants is a practical generic means to prevent this stress-induced aggregation (e.g. in formulations of therapeutic proteins), which suggests that interfaces contribute to destabilization. We studied here the role of interfacial stress by applying brief mechanical impacts on the air-water interface, in the presence or absence of surfactants, in solutions of immunoglobulin G (IgG), a class of proteins of high importance to the developments of new therapeutics. A variety of surfactants was tested including the neutral ones Tween80, C10-C14 fos-cholines, alkylaminoxide, surfactin, and two ionic ones, TTAB and lauroylsarcosine sodium salt. We determined the presence of aggregates in solution by light scattering. Irrespective of the type of antibody, either human polyclonal or a monoclonal one, we show that the amount of aggregated IgG increases in proportion to the number of impacts on the interface. In the absence of stress, we recorded images of oblate aggregates of IgG (ca. 12 nm height and 200-1200 nm diameter) present at the air-water interface (fluorescence microscopy using anti-Fab or anti-Fc markers, and AFM scans after transfer on freshly cleaved mica). Our results evidence that aggregates are formed at the air-water interface, and are brought in solution by transient stresses applied on the water surface. Rupture of interfacial films is an important source of aggregates in solution. Finally, the role of surface dynamics in the protection brought by surfactants is discussed based on the comparison of protective efficiencies with dynamic surface tension properties (measured by the maximum bubble pressure method). Our work indicates that better protection is conferred by surfactants showing the faster interfacial dynamics, which corresponds also to conditions of faster lowering of the interfacial energy at a short time scale

The Video Mesh: A Data Structure for Image-based Video Editing

This paper introduces the video mesh, a data structure for representing video as 2.5D "paper cutouts." The video mesh allows interactive editing of moving objects and modeling of depth, which enables 3D effects and post-exposure camera control. The video mesh sparsely encodes optical flow as well as depth, and handles occlusion using local layering and alpha mattes. Motion is described by a sparse set of points tracked over time. Each point also stores a depth value. The video mesh is a triangulation over this point set and per-pixel information is obtained by interpolation. The user rotoscopes occluding contours and we introduce an algorithm to cut the video mesh along them. Object boundaries are refined with perpixel alpha values. The video mesh is at its core a set of texture mapped triangles, we leverage graphics hardware to enable interactive editing and rendering of a variety of effects. We demonstrate the effectiveness of our representation with a number of special effects including 3D viewpoint changes, object insertion, and depth-of-field manipulation

The Video Mesh: A Data Structure for Image-based Three-dimensional Video Editing

This paper introduces the video mesh, a data structure for representing video as 2.5D “paper cutouts.” The video mesh allows interactive editing of moving objects and modeling of depth, which enables 3D effects and post-exposure camera control. The video mesh sparsely encodes optical flow as well as depth, and handles occlusion using local layering and alpha mattes. Motion is described by a sparse set of points tracked over time. Each point also stores a depth value. The video mesh is a triangulation over this point set and per-pixel information is obtained by interpolation. The user rotoscopes occluding contours and we introduce an algorithm to cut the video mesh along them. Object boundaries are refined with per-pixel alpha values. The video mesh is at its core a set of texture mapped triangles, we leverage graphics hardware to enable interactive editing and rendering of a variety of effects. We demonstrate the effectiveness of our representation with special effects such as 3D viewpoint changes, object insertion, depth-of-field manipulation, and 2D to 3D video conversion

Experimental study of work fluctuations in a harmonic oscillator

The work fluctuations of a harmonic oscillator in contact with a thermostat and driven out of equilibrium by an external force are studied experimentally. For the work both the transient and stationary state fluctuation theorems hold. The finite time corrections are very different from those of a first order Langevin equation. The heat and work fluctuations are studied when a periodic forcing is applied to the oscillator. The importance of the choice of the ''good work'' to compute the free energy from the Jarzinsky equality is discussed

Connected Tropical Subgraphs in Vertex-Colored Graphs

International audienceA subgraph of a vertex-colored graph is said to be tropical whenever it contains each color of the graph. In this work we study the problem of finding a minimal connected tropical subgraph. We first show that this problem is NP-Hard for trees, interval graphs and split graphs, but polynomial when the number of colors is logarithmic in terms of the order of the graph (i.e. FPT). We then provide upper bounds for the order of the minimal connected tropical subgraph under various conditions. We finally study the problem of finding a connected tropical subgraph in a randomly vertex-colored random graph

The Head Turning Modulation System: An Active Multimodal Paradigm for Intrinsically Motivated Exploration of Unknown Environments

Over the last 20 years, a significant part of the research in exploratory robotics partially switches from looking for the most efficient way of exploring an unknown environment to finding what could motivate a robot to autonomously explore it. Moreover, a growing literature focuses not only on the topological description of a space (dimensions, obstacles, usable paths, etc.) but rather on more semantic components, such as multimodal objects present in it. In the search of designing robots that behave autonomously by embedding life-long learning abilities, the inclusion of mechanisms of attention is of importance. Indeed, be it endogenous or exogenous, attention constitutes a form of intrinsic motivation for it can trigger motor command toward specific stimuli, thus leading to an exploration of the space. The Head Turning Modulation model presented in this paper is composed of two modules providing a robot with two different forms of intrinsic motivations leading to triggering head movements toward audiovisual sources appearing in unknown environments. First, the Dynamic Weighting module implements a motivation by the concept of Congruence, a concept defined as an adaptive form of semantic saliency specific for each explored environment. Then, the Multimodal Fusion and Inference module implements a motivation by the reduction of Uncertainty through a self-supervised online learning algorithm that can autonomously determine local consistencies. One of the novelty of the proposed model is to solely rely on semantic inputs (namely audio and visual labels the sources belong to), in opposition to the traditional analysis of the low-level characteristics of the perceived data. Another contribution is found in the way the exploration is exploited to actively learn the relationship between the visual and auditory modalities. Importantly, the robot—endowed with binocular vision, binaural audition and a rotating head—does not have access to prior information about the different environments it will explore. Consequently, it will have to learn in real-time what audiovisual objects are of “importance” in order to rotate its head toward them. Results presented in this paper have been obtained in simulated environments as well as with a real robot in realistic experimental conditions