Ganesh Ramakrishnan
Artificial Intelligence · 2009–2023
A researcher in the Science corpus: 12 papers; trusts 208 researchers and is trusted by 24 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 151 citations into it; #9,150 of 35,345 by trust here, #10,430 by citations
- Natural Language Processing — 74 citations into it; #2,638 of 5,688 by trust here, #4,361 by citations
- Computer Vision and Pattern Recognition — 72 citations into it; #15,687 of 21,575 by trust here, #14,478 by citations
- Evaluation & Benchmarks — 26 citations into it
- Optimization & Training — 25 citations into it
- Information Systems — 18 citations into it; #1,795 of 8,771 by trust here, #2,539 by citations
- Model Architectures — 17 citations into it
- Computational Theory and Mathematics — 16 citations into it
Whom Ganesh Ramakrishnan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Yoshua Bengio
- Diederik P. Kingma
- Geoffrey E. Hinton
- Kaiming He
- Oriol Vinyals
- Dzmitry Bahdanau
- Yann LeCun
- Ilya Sutskever
- Justus J. Randolph
Who trusts Ganesh Ramakrishnan overall
- Shiyue Zhang
- Vishwajeet Kumar
- Zhaochen Guo
- Mohit Bansal
- Tom Hosking
- Amit Singh
- Partha P. Talukdar
- Dmitry M. Malioutov
- Johannes Hoffart
- Krishnateja Killamsetty
Papers from Ganesh Ramakrishnan's perspective
Ordered by how strongly the researchers Ganesh Ramakrishnan 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- 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
- GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training (2021) — 337 citations
- Cross-Modal learning for Audio-Visual Video Parsing (2021) — 9 citations
- Collective annotation of Wikipedia entities in web text (2009) — 496 citations
- Cross-Lingual Training for Automatic Question Generation (2019) — 61 citations
- Putting the Horse before the Cart: A Generator-Evaluator Framework for Question Generation from Text (2018) — 44 citations
- Learning to rank for quantity consensus queries (2009) — 30 citations
- When Do Neural Nets Outperform Boosted Trees on Tabular Data? (2023) — 356 citations
- GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training (2021) — 81 citations
- A Weakly Supervised Model for Solving Math word Problems (2021) — 6 citations
- GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning (2020) — 324 citations
- A framework for automatic question generation from text using deep reinforcement learning (2018) — 47 citations
- Efficient Rule Ensemble Learning using Hierarchical Kernels (2011) — 27 citations