Novel transformation-based response prediction of shear building using interval neural network
By Snehashish Chakraverty, Deepti Moyi Sahoo. 2017
5 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Civil and Structural Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Jacek Tabor
- Przemyslaw Spurek
- Tomasz Trzcinski
- Lukasz Pustelnik
- Bartosz W'ojcik
- Magdalena Proszewska
- Pawel Morawiecki
- Karol J. Piczak
In Civil and Structural Engineering
- Jacek Tabor
- Przemyslaw Spurek
- Tomasz Trzcinski
- Lukasz Pustelnik
- Bartosz W'ojcik
- Magdalena Proszewska
- Pawel Morawiecki
- Karol J. Piczak
Citations in the corpus
- Continual Learning with Guarantees via Weight Interval Constraints (2022, methodology): “This architecture was further adapted for viruses data with uncertainty modeled by intervals (Chakraverty & Sahoo, 2017; Sahoo & Chakraverty, 2020).”
- HyperCube: Implicit Field Representations of Voxelized 3D Models (2021, methodology): “In neural networks interval arithmetic is used to train models on interval data [38, 39, 40] and produce neural networks that are robust against adversarial attacks [2, 3].”