Po-Yao (Bernie) Huang

Computer Vision and Pattern Recognition · 2016–2024

A researcher in the Science corpus: 13 papers; trusts 1,239 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 612 citations into it; #13,267 of 21,575 by trust here, #2,494 by citations
• Artificial Intelligence — 576 citations into it; #17,785 of 35,345 by trust here, #3,111 by citations
• Natural Language Processing — 160 citations into it; #3,906 of 5,688 by trust here, #3,897 by citations
• Representation & Self-Supervised Learning — 153 citations into it; #3,090 of 3,145 by trust here, #1,202 by citations
• Multimodal Learning — 127 citations into it; #706 of 1,211 by trust here, #261 by citations
• Model Architectures — 103 citations into it
• Evaluation & Benchmarks — 100 citations into it
• Large Language Models — 62 citations into it

Whom Po-Yao (Bernie) Huang trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Ilya Sutskever
6. Yoshua Bengio
7. Ross B. Girshick
8. Yann LeCun
9. Shaoqing Ren
10. Karen Simonyan

Who trusts Po-Yao (Bernie) Huang overall

1. Felix Stahlberg
2. Jean-Benoit Delbrouck
3. Iacer Calixto
4. Mandela Patrick
5. Pranava Swaroop Madhyastha
6. Aditya Mogadala
7. Emanuele Bugliarello
8. Yuying Ge
9. Hu Xu
10. Rachel Bawden

Papers from Po-Yao (Bernie) Huang's perspective

Ordered by how strongly the researchers Po-Yao (Bernie) Huang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• DINOv2: Learning Robust Visual Features without Supervision (2023) — 9,372 citations
• VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding (2021) — 814 citations
• Support-set bottlenecks for video-text representation learning (2020) — 271 citations
• CM3: A Causal Masked Multimodal Model of the Internet (2022) — 180 citations
• VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding (2021) — 158 citations
• Multilingual Multimodal Pre-training for Zero-Shot Cross-Lingual Transfer of Vision-Language Models (2021) — 64 citations
• Masked Autoencoders that Listen (2022) — 474 citations
• Attention-based Multimodal Neural Machine Translation (2016) — 183 citations
• Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles (2023) — 437 citations
• Unsupervised Multimodal Neural Machine Translation with Pseudo Visual Pivoting (2020) — 57 citations
• The Llama 3 Herd of Models (2024) — 17,085 citations
• A Comprehensive Survey of Neural Architecture Search (2020) — 868 citations
• A Survey of Deep Active Learning (2020) — 1,521 citations