Yunbo Wang

Computer Vision and Pattern Recognition · Neural Information Processing Systems · 2017–2021

A researcher in the Science corpus: 5 papers; trusts 343 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 118 citations into it
• Artificial Intelligence — 68 citations into it
• Generative Models — 55 citations into it
• Model Architectures — 33 citations into it
• Optimization & Training — 18 citations into it
• Natural Language Processing — 15 citations into it
• Reinforcement Learning — 14 citations into it
• Representation & Self-Supervised Learning — 13 citations into it

Whom Yunbo Wang trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Ilya Sutskever
4. Alex Graves
5. Alex Krizhevsky
6. Yoshua Bengio
7. Yann LeCun
8. Jimmy Ba
9. Sepp Hochreiter
10. Oriol Vinyals

Who trusts Yunbo Wang overall

1. Vincent Le Guen
2. Zhangyang Gao
3. Zhihui Lin
4. Sergiu Oprea
5. Nicolas Thomé
6. Kevin Trebing
7. Cheng Tan
8. Haixu Wu
9. Jianjin Zhang
10. Zhihan Gao

Papers from Yunbo Wang's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning (2021) — 647 citations
• Eidetic 3D LSTM: A Model for Video Prediction and Beyond (2019) — 439 citations
• Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics (2018) — 422 citations
• PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning (2018) — 613 citations
• PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs (2017) — 1,007 citations