Shalmali Joshi
Artificial Intelligence · 2018–2021
A researcher in the Science corpus: 6 papers; trusts 137 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 131 citations into it; #26,741 of 35,345 by trust here, #11,921 by citations
- Safety, Robustness & Interpretability — 80 citations into it
- Computer Vision and Pattern Recognition — 31 citations into it; #18,532 of 21,575 by trust here, #18,782 by citations
- Health Informatics — 20 citations into it
- Statistics and Probability — 19 citations into it
- Safety Research — 17 citations into it
- Natural Language Processing — 15 citations into it
- AI Ethics, Fairness & Society — 11 citations into it
Whom Shalmali Joshi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Jeff Donahue
- Kaiming He
- Marco Tulio Ribeiro
- Been Kim
- Yann LeCun
- Ilya Sutskever
Who trusts Shalmali Joshi overall
- Peter Hase
- Sahil Verma
- Divyat Mahajan
- Stephen Casper
- Vivian Lai
- Amir-Hossein Karimi
- Mohit Bansal
- Chenhao Tan
- Aniek F. Markus
- John P. Dickerson
Papers from Shalmali Joshi's perspective
Ordered by how strongly the researchers Shalmali Joshi 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)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- xGEMs: Generating Examplars to Explain Black-Box Models (2018) — 42 citations
- Sequential Explanations with Mental Model-Based Policies (2020) — 16 citations
- Ethical Machine Learning in Healthcare (2020) — 577 citations
- Towards Robust and Reliable Algorithmic Recourse (2021) — 136 citations
- What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use (2019) — 663 citations
- Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems (2019) — 225 citations