Shruti Tople

Artificial Intelligence · 2016–2023

A researcher in the Science corpus: 7 papers; trusts 319 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 223 citations into it; #15,662 of 35,345 by trust here, #10,207 by citations
• Safety, Robustness & Interpretability — 73 citations into it; #1,036 of 2,251 by trust here, #1,078 by citations
• Privacy & Security — 61 citations into it; #357 of 709 by trust here, #434 by citations
• Computer Vision and Pattern Recognition — 58 citations into it
• Optimization & Training — 30 citations into it
• Representation & Self-Supervised Learning — 30 citations into it
• Large Language Models — 22 citations into it
• Natural Language Processing — 21 citations into it

Whom Shruti Tople trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yann LeCun
4. L. Eon Bottou
5. Diederik P. Kingma
6. Yoshua Bengio
7. Kaiming He
8. Cynthia Dwork
9. Ilya Sutskever
10. J. Urgen Schmidhuber

Who trusts Shruti Tople overall

1. Clement Fung
2. Muhammad Shayan
3. Chien-Lun Chen
4. Moran Baruch
5. Xiaoyu Cao
6. Zhiyi Tian
7. Aidmar Wainakh
8. T. D. Nguyen
9. Kathrin Grosse
10. Jindong Wang

Papers from Shruti Tople's perspective

Ordered by how strongly the researchers Shruti Tople trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Analyzing Information Leakage of Updates to Natural Language Models (2019) — 147 citations
• Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning (2020) — 389 citations
• Auror: defending against poisoning attacks in collaborative deep learning systems (2016) — 365 citations
• Analyzing Leakage of Personally Identifiable Information in Language Models (2023) — 411 citations
• AN EMPIRICAL STUDY (2022)
• Domain Generalization using Causal Matching (2020) — 409 citations
• On the Intrinsic Privacy of Stochastic Gradient Descent (2019) — 13 citations