59 citations
- Schlumberger (United States)US2 papers
- University of GenevaCH2 papers
- Centre de Robotique1 paper
- Centre de Robotique Intégrée d'Ile de FranceFR1 paper
- École Nationale Supérieure des Mines de ParisFR1 paper
- Georgia Institute of TechnologyUS1 paper
- Imperial College LondonGB1 paper
- Johns Hopkins UniversityUS1 paper
- Los Alamos National LaboratoryUS1 paper
- Nanyang Technological UniversitySG1 paper
- Schlumberger (United Kingdom)GB1 paper
- The Abdus Salam International Centre for Theoretical Physics (ICTP)IT1 paper
12 papers
Scaling rules for multiphase flow in vertical Venturis
Meng-Ke Zhan, Cheng-Gang Xie, Jian-Jun Shu
Employing a suitable scaling rule in gas-liquid flow can produce dynamically comparable results, which helps in the development of flow models applicable to a wide range of flow co…
A simulation-free seismic survey design by maximizing the spectral gap
Yijun Zhang, Mathias Louboutin, Ali Siahkoohi +3
Due to the tremendous cost of seismic data acquisition, methods have been developed to reduce the amount of data acquired by designing optimal missing trace reconstruction algorith…
Droplets with circular stagnation lines: combined effects of viscoelastic and inertial forces on drop shapes
A. Emamian M. Norouzi, M. Davoodi
Hydrodynamic problems with stagnation points are of particular importance in fluid mechanics as they allow study and investigation of elongational flows. In this article, the uniax…
Unsupervised clustering of series using dynamic programming and neural processes
Karthigan Sinnathamby, Chang-Yu Hou, Lalitha Venkataramanan +2
Following the work of arXiv:2101.09512, we are interested in clustering a given multi-variate series in an unsupervised manner. We would like to segment and cluster the series such…
Unsupervised clustering of series using dynamic programming
Karthigan Sinnathamby, Chang-Yu Hou, Lalitha Venkataramanan +2
We are interested in clustering parts of a given single multi-variate series in an unsupervised manner. We would like to segment and cluster the series such that the resulting bloc…
Machine learning applied in the multi-scale 3D stress modelling
Xavier Garcia, Adrian Rodriguez-Herrera
This paper proposes a methodology to estimate stress in the subsurface by a hybrid method combining finite element modeling and neural networks. This methodology exploits the idea…