Xinhao Mei
Computer Vision and Pattern Recognition · 2023
A researcher in the Science corpus: 3 papers; trusts 53 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 99 citations into it
- Artificial Intelligence — 87 citations into it
- Signal Processing — 79 citations into it
- Generative Models — 49 citations into it
- Statistical and Nonlinear Physics — 17 citations into it
- Optimization & Training — 5 citations into it
- Probabilistic & Bayesian Methods — 5 citations into it
Whom Xinhao Mei trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Jimmy Ba
- Kaiming He
- Jonathan Ho
- Ilya Sutskever
- Yann LeCun
- Alex Graves
Who trusts Xinhao Mei overall
Papers from Xinhao Mei's perspective
Ordered by how strongly the researchers Xinhao Mei 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- 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
- AudioLDM: Text-to-Audio Generation with Latent Diffusion Models (2023) — 854 citations
- AudioLDM 2: Learning Holistic Audio Generation With Self-Supervised Pretraining (2023) — 512 citations
- WavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal Research (2023) — 418 citations