Ramin Bostanabad
Mechanics of Materials · 2017–2019
A researcher in the Science corpus: 4 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Mechanics of Materials — 43 citations into it
- Computational Theory and Mathematics — 38 citations into it
- Statistics and Probability — 25 citations into it
- Artificial Intelligence — 24 citations into it
- Computer Vision and Pattern Recognition — 21 citations into it
- Optimization & Training — 6 citations into it
Whom Ramin Bostanabad trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ilya M. Sobol
- B. A. Le
- Julien Yvonnet
- Grace Wahba
- Christopher K. I. Williams
- Robert B. Gramacy
- Jeremy S. De Bonet
- B. Thompson
- Anthony OʼHagan
- Andrea Saltelli
Who trusts Ramin Bostanabad overall
Papers from Ramin Bostanabad's perspective
Ordered by how strongly the researchers Ramin Bostanabad trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality (2017) — 525 citations
- Globally Approximate Gaussian Processes for Big Data With Application to Data-Driven Metamaterials Design (2019) — 57 citations
- Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques (2018) — 413 citations
- Deep learning predicts path-dependent plasticity (2019) — 569 citations