Ziniu Hu
Artificial Intelligence · 2017–2023
A researcher in the Science corpus: 7 papers; trusts 196 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 174 citations into it; #21,490 of 35,345 by trust here, #10,319 by citations
- Computer Vision and Pattern Recognition — 80 citations into it; #15,489 of 21,575 by trust here, #11,083 by citations
- Natural Language Processing — 36 citations into it
- Graph Learning — 35 citations into it
- Representation & Self-Supervised Learning — 27 citations into it
- Information Systems — 19 citations into it; #4,596 of 8,771 by trust here, #1,672 by citations
- Statistical and Nonlinear Physics — 17 citations into it
- Information Retrieval & Search — 16 citations into it
Whom Ziniu Hu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Alex Krizhevsky
- Ilya Loshchilov
- Ilya Sutskever
- Ross B. Girshick
- Yann LeCun
- Max Welling
Who trusts Ziniu Hu overall
- Xiao Liu
- Weiwei Jiang
- A. Ozbayoglu
- Omer Berat Sezer
- Haopeng Zhang
- William Grant Hatcher
- Michelle M. Li
- Shuaicheng Zhang
- Yuxiao Dong
- M. Ugur Gudelek
Papers from Ziniu Hu's perspective
Ordered by how strongly the researchers Ziniu Hu 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Reveal: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory (2022) — 178 citations
- Heterogeneous Graph Transformer (2020) — 1,684 citations
- Relation-Guided Pre-Training for Open-Domain Question Answering (2021) — 6 citations
- Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks (2019) — 339 citations
- Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction (2017) — 345 citations
- SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models (2023) — 252 citations
- GPT-GNN: Generative Pre-Training of Graph Neural Networks (2020) — 687 citations