Ratish Puduppully
Artificial Intelligence · 2018–2022
A researcher in the Science corpus: 4 papers; trusts 197 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 119 citations into it; #9,788 of 35,345 by trust here, #11,921 by citations
- Natural Language Processing — 117 citations into it; #1,813 of 5,688 by trust here, #2,263 by citations
- Evaluation & Benchmarks — 40 citations into it
- Computer Vision and Pattern Recognition — 35 citations into it
- Model Architectures — 17 citations into it
- Natural Language Generation — 8 citations into it; #188 of 199 by trust here, #118 by citations
- Generative Models — 6 citations into it
- Optimization & Training — 5 citations into it
Whom Ratish Puduppully trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Oriol Vinyals
- Yoshua Bengio
- Ronald J. Williams
- Geoffrey E. Hinton
- Ilya Sutskever
- John C. Duchi
- Sepp Hochreiter
- Diederik P. Kingma
- Ehud Reiter
- Dzmitry Bahdanau
Who trusts Ratish Puduppully overall
- Hongmin Wang
- Mihir Kale
- Zhiyu Chen
- Craig Thomson
- Mirella Lapata
- Nazneen Rajani
- Hayate Iso
- Wenhu Chen
- Sebastian Gehrmann
- Ehud Reiter
Papers from Ratish Puduppully's perspective
Ordered by how strongly the researchers Ratish Puduppully 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
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Data-to-Text Generation with Content Selection and Planning (2018) — 336 citations
- GEMv2: Multilingual NLG Benchmarking in a Single Line of Code (2022) — 43 citations
- Data-to-text Generation with Macro Planning (2021) — 91 citations
- Data-to-text Generation with Entity Modeling (2019) — 130 citations