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Found 11 papers, 1 papers with code
FO-PINNs: A First-Order formulation for Physics Informed Neural Networks
Physics-Informed Neural Networks (PINNs) are a class of deep learning neural networks that learn the response of a physical system without any simulation data, and only by incorporating the governing partial differential equations (PDEs) in their loss function.
Exact imposition of boundary conditions with distance functions in physics-informed deep neural networks
In this paper, we introduce a new approach based on distance fields to exactly impose boundary conditions in physics-informed deep neural networks.
Scattering under Linear Non Self-Adjoint Operators: Case of in-Plane Elastic Waves
In this paper, we consider the problem of the scattering of in-plane waves at an interface between a homogeneous medium and a metamaterial.
Applied Physics
Cosmological N-body simulations: a challenge for scalable generative models
Our results show that the proposed model produces samples of high visual quality, although the statistical analysis reveals that capturing rare features in the data poses significant problems for the generative models.
Design and Analysis of a Novel Control Moment Gyroscope (CMG) For Small Satellite Applications
This paper presents a novel Single Gimbal Control Moment Gyroscope (CMG) to increase the agility of small satellites while consuming a low power.
Semantic Storytelling, Cross-lingual Event Detection and other Semantic Services for a Newsroom Content Curation Dashboard
We present a prototypical content curation dashboard, to be used in the newsroom, and several of its underlying semantic content analysis components (such as named entity recognition, entity linking, summarisation and temporal expression analysis).
Event Detection and Semantic Storytelling: Generating a Travelogue from a large Collection of Personal Letters
We present an approach at identifying a specific class of events, movement action events (MAEs), in a data set that consists of ca.
DFKI-DKT at SemEval-2017 Task 8: Rumour Detection and Classification using Cascading Heuristics
We describe our submissions for SemEval-2017 Task 8, Determining Rumour Veracity and Support for Rumours.
