Benjamin Moseley

Statistical and Nonlinear Physics · with Markham · 2021

A researcher in the Science corpus: 1 paper; trusts 27 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistical and Nonlinear Physics — 30 citations into it
• Artificial Intelligence — 16 citations into it
• Computational Mechanics — 13 citations into it
• AI for Physical Sciences — 7 citations into it
• Statistics and Probability — 7 citations into it
• Aerospace Engineering — 6 citations into it

Whom Benjamin Moseley trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. G. Em Karniadakis
2. Maizar Raissi
3. Isaac E. Lagaris
4. Liu Yang
5. Lu Lu
6. Sifan Wang
7. Diederik P. Kingma
8. Paris Perdikaris
9. Ameya Dilip Jagtap
10. Dongkun Zhang

Who trusts Benjamin Moseley overall

1. Salvatore Cuomo
2. Vincenzo Schiano Di Cola

Papers from Benjamin Moseley's perspective

Ordered by how strongly the researchers Benjamin Moseley trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Learning Multiple Layers of Features from Tiny Images
8. GENERATIVE ADVERSARIAL NETS
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Finite basis physics-informed neural networks (FBPINNs): a scalable domain decomposition approach for solving differential equations (2021) — 400 citations