Sagnik Majumder
Computer Vision and Pattern Recognition · 2019–2023
A researcher in the Science corpus: 2 papers; trusts 136 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 137 citations into it; #16,493 of 21,575 by trust here, #19,310 by citations
- Artificial Intelligence — 83 citations into it; #26,932 of 35,345 by trust here, #30,347 by citations
- Representation & Self-Supervised Learning — 27 citations into it
- Generative Models — 21 citations into it
- Evaluation & Benchmarks — 19 citations into it
- Meta & Continual Learning — 15 citations into it
- Optimization & Training — 11 citations into it
- Model Architectures — 9 citations into it
Whom Sagnik Majumder trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Alex Graves
- Yann LeCun
- Yoshua Bengio
- Max Welling
- Ilya Sutskever
- Sergey Ioffe
Who trusts Sagnik Majumder overall
Papers from Sagnik Majumder's perspective
Ordered by how strongly the researchers Sagnik Majumder 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)