no code implementations • 25 Oct 2022 • Rini J. Gladstone, Mohammad A. Nabian, N. Sukumar, Ankit Srivastava, Hadi Meidani
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.
no code implementations • 17 Apr 2021 • N. Sukumar, Ankit Srivastava
In this paper, we introduce a new approach based on distance fields to exactly impose boundary conditions in physics-informed deep neural networks.
no code implementations • 6 Mar 2020 • Amir Ashkan Mokhtari, Yan Lu, Qiyuan Zhou, Alireza V. Amirkhizi, Ankit Srivastava
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
1 code implementation • 15 Aug 2019 • Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Réfrégier
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.
no code implementations • 6 Jun 2018 • Mihindukulasooriya Sheral Crescent Tissera, Kay Soon Low, Ankit Srivastava, Abhishek Rai, Jun Hao Tan and Yan Rui Tan
This paper presents a novel Single Gimbal Control Moment Gyroscope (CMG) to increase the agility of small satellites while consuming a low power.
no code implementations • WS 2017 • Julian Moreno-Schneider, Ankit Srivastava, Peter Bourgonje, David Wabnitz, Georg Rehm
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).
no code implementations • WS 2017 • Georg Rehm, Julian Moreno Schneider, Peter Bourgonje, Ankit Srivastava, Jan Nehring, Armin Berger, Luca K{\"o}nig, S{\"o}ren R{\"a}uchle, Jens Gerth
We present an approach at identifying a specific class of events, movement action events (MAEs), in a data set that consists of ca.
no code implementations • SEMEVAL 2017 • Ankit Srivastava, Georg Rehm, Julian Moreno Schneider
We describe our submissions for SemEval-2017 Task 8, Determining Rumour Veracity and Support for Rumours.