Karthikeyan Natesan Ramamurthy
Artificial Intelligence · 2015–2023
A researcher in the Science corpus: 14 papers; trusts 57 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 194 citations into it; #24,160 of 35,345 by trust here, #8,157 by citations
- Safety, Robustness & Interpretability — 93 citations into it; #1,581 of 2,251 by trust here, #729 by citations
- Safety Research — 69 citations into it
- AI Ethics, Fairness & Society — 47 citations into it; #225 of 494 by trust here, #86 by citations
- Natural Language Processing — 42 citations into it
- Computer Vision and Pattern Recognition — 39 citations into it; #15,059 of 21,575 by trust here, #15,955 by citations
- Sociology and Political Science — 24 citations into it
- Information Systems — 17 citations into it
Whom Karthikeyan Natesan Ramamurthy trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Faisal Kamiran
- Toon Calders
- Geoffrey E. Hinton
- David G. Lowe
- Moritz Hardt
- Yoshua Bengio
- Alex Krizhevsky
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
Who trusts Karthikeyan Natesan Ramamurthy overall
Papers from Karthikeyan Natesan Ramamurthy's perspective
Ordered by how strongly the researchers Karthikeyan Natesan Ramamurthy 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- 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)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Optimized Data Pre-Processing for Discrimination Prevention (2017) — 64 citations
- The Impact of Positional Encoding on Length Generalization in Transformers (2023) — 396 citations
- FactSheets: Increasing trust in AI services through supplier's declarations of conformity (2019) — 370 citations
- Your fairness may vary: Pretrained language model fairness in toxic text classification (2021) — 61 citations
- Increasing Trust in AI Services through Supplier's Declarations of Conformity (2018) — 136 citations
- AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019) — 755 citations
- Fair Transfer Learning with Missing Protected Attributes (2019) — 123 citations
- TED: Teaching AI to Explain its Decisions (2018) — 115 citations
- FactSheets: Increasing Trust in AI Services through Supplier's Declarations of Conformity. (2018) — 7 citations
- AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias (2018) — 944 citations
- Bias Mitigation Post-processing for Individual and Group Fairness (2018) — 193 citations
- Optimized Pre-Processing for Discrimination Prevention (2017) — 843 citations
- TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning (2016) — 44 citations
- Adaptive as-natural-as-possible image stitching (2015) — 364 citations