Apoorv Saxena
Artificial Intelligence · 2020–2021
A researcher in the Science corpus: 2 papers; trusts 65 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 43 citations into it; #32,141 of 35,345 by trust here, #20,377 by citations
- Natural Language Processing — 24 citations into it
- Computer Vision and Pattern Recognition — 11 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
- Question Answering & Reading Comprehension — 7 citations into it; #283 of 335 by trust here, #225 by citations
- Graph Learning — 6 citations into it
Whom Apoorv Saxena trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Antoine Bordes
- Jason Aaron Edward Weston
- Haitian Sun
- Nicolas Usunier
- Yoshua Bengio
- Geoffrey E. Hinton
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Wen-tau Yih
Who trusts Apoorv Saxena overall
- Linhao Luo
- Xi Ye
- Jing Zhang
- Weiwen Xu
- Bhuwan Dhingra
- Jinhao Jiang
- Hongyu Ren
- Soumen Chakrabarti
- Tianbao Xie
- Yuan-Fang Li
Papers from Apoorv Saxena's perspective
Ordered by how strongly the researchers Apoorv Saxena trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings (2020) — 644 citations
- Question Answering Over Temporal Knowledge Graphs (2021) — 203 citations