Weiqiang Zhu
Artificial Intelligence · 2018–2021
A researcher in the Science corpus: 6 papers; trusts 48 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 54 citations into it; #10,926 of 35,345 by trust here, #16,166 by citations
- Geophysics — 43 citations into it; #283 of 1,958 by trust here, #500 by citations
- Computer Vision and Pattern Recognition — 25 citations into it
- Model Architectures — 19 citations into it
- Natural Language Processing — 11 citations into it
- Optimization & Training — 9 citations into it
- Media Technology — 5 citations into it
Whom Weiqiang Zhu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David Martin Ward Powers
- Zachary E. Ross
- S. M. Mousavi
- Olaf Ronneberger
- Radford M. Neal
- Diederik P. Kingma
- Gregory C. Beroza
- Roger Fletcher
- Men‐Andrin Meier
- T. Perol
Who trusts Weiqiang Zhu overall
Papers from Weiqiang Zhu's perspective
Ordered by how strongly the researchers Weiqiang Zhu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- 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
- Earthquake Phase Association Using a Bayesian Gaussian Mixture Model (2021) — 144 citations
- Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking (2020) — 973 citations
- STanford EArthquake Dataset (STEAD): A Global Data Set of Seismic Signals for AI (2019) — 368 citations
- Seismic Signal Denoising and Decomposition Using Deep Neural Networks (2018) — 406 citations
- CRED: A Deep Residual Network of Convolutional and Recurrent Units for Earthquake Signal Detection (2018) — 316 citations
- PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method (2018) — 1,143 citations