Aditya Mogadala

Computer Vision and Pattern Recognition · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 1,294 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 267 citations into it
• Artificial Intelligence — 215 citations into it; #21,125 of 35,345 by trust here, #25,809 by citations
• Multimodal Learning — 138 citations into it
• Natural Language Processing — 127 citations into it
• Evaluation & Benchmarks — 32 citations into it
• Generative Models — 26 citations into it
• Representation & Self-Supervised Learning — 24 citations into it
• Model Architectures — 16 citations into it

Whom Aditya Mogadala trusts overall

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

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

Who trusts Aditya Mogadala overall

1. Mikel Artetxe
2. Holger Schwenk
3. Jabeen Summaira
4. Gorka Labaka
5. Eneko Agirre
6. Sebastian Ruder
7. Stanislav Frolov
8. Xi Li

Papers from Aditya Mogadala's perspective

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

Their papers

• Bilingual Word Embeddings from Parallel and Non-parallel Corpora for Cross-Language Text Classification (2016) — 89 citations
• Investigating the Impact of Pre-trained Word Embeddings on Memorization in Neural Networks (2020) — 39 citations
• Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods (2019) — 148 citations