Blogue
3D Deep-learning-based Segmentation of Human Skin Sweat Glands and Their 3D Morphological Response to Temperature Variations
Skin, the primary regulator of heat exchange, relies on sweat glands for thermoregulation. Alterations in sweat gland morphology play a crucial role in various pathological conditions and clinical diagnoses. Current methods for observing sweat gland morphology are limited by their two-dimensional, dans...
Towards Generalized and Training-Free Text-Guided Semantic Manipulation
Text-guided semantic manipulation refers to semantically editing an image generated from a source prompt to match a target prompt, enabling the desired semantic changes (par ex., ajout, removal, and style transfer) while preserving irrelevant contents. With the powerful generative capabilities of the diffusion...
Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors
Machine learning methods are being introduced at all stages of data reconstruction and analysis in various high-energy physics experiments. We present the development and application of convolutional neural networks with modified autoencoder architecture for the reconstruction of the pulse arrival time and...
EdgePoint2: Compact Descriptors for Superior Efficiency and Accuracy
The field of keypoint extraction, which is essential for vision applications like Structure from Motion (SfM) and Simultaneous Localization and Mapping (SLAM), has evolved from relying on handcrafted methods to leveraging deep learning techniques. While deep learning approaches have significantly improved performance,...
Separating Two Points with Obstacles in the Plane: Improved Upper and Lower Bounds
Given two points in the plane, and a set of “obstacles” given as curves through the plane with assigned weights, we consider the point-separation problem, which asks for the minimum-weight subset of the obstacles separating the two points. A few computational models...
Intermittency and non-universality of pair dispersion in isothermal compressible turbulence
Statistical properties of the pair dispersion of Lagrangian particles (tracers) in incompressible turbulent flows provide insights into transport and mixing. We explore the same in transonic to supersonic compressible turbulence of an isothermal ideal gas in two dimensions, driven by large-scale solenoidal...
Effective field theory of coupled dark energy and dark matter
We formulate an effective field theory (EFT) of coupled dark energy (DE) and dark matter (DM) interacting through energy and momentum transfers. In the DE sector, we exploit the EFT of vector-tensor theories with the presence of a preferred time direction on...
Enhancing the controllability of quantum systems via a static field
In this paper we discuss how a general bilinear finite-dimensional closed quantum system with dispersed parameters can be steered between eigenstates. Nous montrons que, under suitable conditions on the separation of spectral gaps and the boundedness of parameter dispersion, rotating wave and...
You Are What You Bought: Generating Customer Personas for E-commerce Applications
In e-commerce, user representations are essential for various applications. Existing methods often use deep learning techniques to convert customer behaviors into implicit embeddings. Cependant, these embeddings are difficult to understand and integrate with external knowledge, limiting the effectiveness of applications such as...
Physics-based super-resolved simulation of 3D elastic wave propagation adopting scalable Diffusion Transformer
Dans cette étude, we develop a Diffusion Transformer (referred as to DiT1D) for synthesizing realistic earthquake time histories. The DiT1D generates realistic broadband accelerograms (0-30 Hz resolution), constrained at low frequency by 3-dimensional (3D) elastodynamics numerical simulations, ensuring the fulfillment of the...