Ramaravind Kommiya Mothilal

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 21 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it; #11,661 of 35,345 by trust here, #14,718 by citations
• Safety, Robustness & Interpretability — 18 citations into it; #808 of 2,251 by trust here, #1,290 by citations
• Communication — 9 citations into it
• Statistical and Nonlinear Physics — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Sociology and Political Science — 5 citations into it

Whom Ramaravind Kommiya Mothilal trusts overall

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

1. Diederik P. Kingma
2. Alex Kulesza
3. Julia Dressel
4. Matevz Kunaver
5. R. Caruana
6. Marco Tulio Ribeiro
7. Sandra Wachter
8. Chris Russell
9. Yin Lou
10. Jimmy Ba

Who trusts Ramaravind Kommiya Mothilal overall

1. Q. Liao
2. Amir-Hossein Karimi
3. Christoph Molnar
4. Sahil Verma
5. Divyat Mahajan
6. Susanne Dandl
7. Ana Lucic
8. Yongming Rao
9. Roberto Confalonieri
10. Bernhard Schölkopf

Papers from Ramaravind Kommiya Mothilal's perspective

Ordered by how strongly the researchers Ramaravind Kommiya Mothilal 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Explaining machine learning classifiers through diverse counterfactual explanations (2019) — 1,400 citations
• Birds of a Caste - How Caste Hierarchies Manifest in Retweet Behavior of Indian Politicians (2020) — 25 citations