Automated Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

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Understanding the high-dimensional chaotic dynamics occurring in complex biological systems such as recurrent neural networks or ecosystems remains a conceptual challenge. For low-dimensional dynamics, fixed points provide the geometric scaffold of the dyn ...

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Diffusion Magnetic Resonance Imaging (dMRI) is a powerful non-invasive method for studying white matter tracts of the brain. However, accurate microstructure estimation with fiber orientation distribution (FOD) using existing computational methods requires ...

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We present a novel method to perform numerical integration over curved polyhedra enclosed by high-order parametric surfaces. Such a polyhedron is first decomposed into a set of triangular and/or rectangular pyramids, whose certain faces correspond to the g ...

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Algorithms are everywhere. The recipe for the frangipane cake is an algorithm. If all the listed ingredients are available and the cook is sufficiently deft, after a finite number of small, well-defined steps a delicious dessert will exit the oven. Now, wh ...

Automated Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Chattez avec Graph Search

Fixed point geometry in chaotic neural networks

Wear across scales

Towards Trustworthy Deep Learning for Image Reconstruction

Predicting protein interactions using geometric deep learning on protein surfaces

GEMTELLIGENCE: Accelerating gemstone classification with deep learning

Mapping drivers of tropical forest loss with satellite image time series and machine learning

An end-to-end pipeline for historical censuses processing

Combining Weather Station Data and Short-Term LiDAR Deployment to Estimate Wind Energy Potential with Machine Learning: A Case Study from the Swiss Alps

Neural and algorithmic bases of odor guided trail following in mice

Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union

Deep Learning Meets Sparse Regularization

A Comparison of Residual-based Methods on Fault Detection

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

Predicting the liveability of Dutch cities with aerial images and semantic intermediate concepts

DISCO: Distilling Counterfactuals with Large Language Models

DeePMD-kit v2: A software package for deep potential models

Impact of Video Processing Operations in Deepfake Detection

Robust numerical integration on curved polyhedra based on folded decompositions

Large-scale traffic signal control and multimodal network design

Practical Byzantine-resilient Stochastic Gradient Descent