Somshubra Majumdar

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 3 papers; trusts 24 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 40 citations into it; #24,266 of 35,345 by trust here, #20,836 by citations
• Signal Processing — 23 citations into it; #5,019 of 7,572 by trust here, #3,784 by citations
• Model Architectures — 17 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Natural Language Processing — 10 citations into it
• Optimization & Training — 6 citations into it
• Economics and Econometrics — 5 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Somshubra Majumdar trusts overall

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

1. Alex Graves
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Kaiming He
6. Jimmy Ba
7. Gary King
8. Sergey Ioffe
9. Alex Krizhevsky
10. Dzmitry Bahdanau

Who trusts Somshubra Majumdar overall

1. Xuchao Zhang
2. Adil Rasheed
3. Alvarez-Vanhard Emilien
4. Alejandro Pasos Ruiz
5. Yifeng Gao
6. Fazle Karim

Papers from Somshubra Majumdar's perspective

Ordered by how strongly the researchers Somshubra Majumdar 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. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• SPGISpeech: 5, 000 hours of transcribed financial audio for fully formatted end-to-end speech recognition (2021) — 113 citations
• Multivariate LSTM-FCNs for Time Series Classification (2018) — 1,048 citations
• LSTM Fully Convolutional Networks for Time Series Classification (2017) — 1,303 citations