Anusha Balakrishnan

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 5 papers; trusts 125 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 97 citations into it; #22,108 of 35,345 by trust here, #9,170 by citations
• Natural Language Processing — 77 citations into it; #3,730 of 5,688 by trust here, #2,031 by citations
• Computer Vision and Pattern Recognition — 21 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Reinforcement Learning — 13 citations into it
• Model Architectures — 12 citations into it
• Management Science and Operations Research — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Anusha Balakrishnan trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Ilya Sutskever
5. Dzmitry Bahdanau
6. Sepp Hochreiter
7. Christopher D. Manning
8. Alex Krizhevsky
9. Ronald J. Williams
10. J. Urgen Schmidhuber

Who trusts Anusha Balakrishnan overall

1. Daniel Kang
2. Emily Sheng
3. Symon Jory Stevens-Guille
4. Jinjie Ni
5. Xiaoyu Shen
6. Yangming Li
7. Peyman Heidari
8. Denis Yarats
9. Tong Niu
10. Tatsunori B. Hashimoto

Papers from Anusha Balakrishnan's perspective

Ordered by how strongly the researchers Anusha Balakrishnan 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings (2017) — 210 citations
• Constrained Decoding for Neural NLG from Compositional Representations in Task-Oriented Dialogue (2019) — 87 citations
• Decoupling Strategy and Generation in Negotiation Dialogues (2018) — 249 citations
• Recommendation as a Communication Game: Self-Supervised Bot-Play for Goal-oriented Dialogue (2019) — 125 citations
• A Tree-to-Sequence Model for Neural NLG in Task-Oriented Dialog (2019) — 14 citations