Subhankar Ghosh

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 3 papers; trusts 162 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 47 citations into it
• Artificial Intelligence — 46 citations into it
• Meta & Continual Learning — 14 citations into it
• Reinforcement Learning — 9 citations into it
• Media Technology — 7 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Generative Models — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Subhankar Ghosh trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Jimmy Ba
5. Yann LeCun
6. Yoshua Bengio
7. Ivan Skorokhodov
8. Max Welling
9. Kaiming He
10. Marc'Aurelio Ranzato

Who trusts Subhankar Ghosh overall

1. Liyuan Wang

Papers from Subhankar Ghosh's perspective

Ordered by how strongly the researchers Subhankar Ghosh 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Effects of Degradations on Deep Neural Network Architectures (2018) — 167 citations
• Dynamic VAEs with Generative Replay for Continual Zero-shot Learning (2021) — 8 citations
• Adversarial Training of Variational Auto-encoders for Continual Zero-shot Learning(A-CZSL) (2021) — 12 citations