Atul Prakash
Artificial Intelligence · 2016–2019
A researcher in the Science corpus: 10 papers; trusts 66 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 114 citations into it; #16,376 of 35,345 by trust here, #4,336 by citations
- Safety, Robustness & Interpretability — 93 citations into it; #1,399 of 2,251 by trust here, #286 by citations
- Computer Vision and Pattern Recognition — 79 citations into it
- Signal Processing — 46 citations into it; #4,588 of 7,572 by trust here, #638 by citations
- Information Systems — 21 citations into it; #6,915 of 8,771 by trust here, #4,885 by citations
- Sociology and Political Science — 7 citations into it
Whom Atul Prakash trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ian J. Goodfellow
- Alex Krizhevsky
- Christian Szegedy
- Geoffrey E. Hinton
- Adrienne Porter Felt
- Yann LeCun
- Nicolas Papernot
- Yoshua Bengio
- Ross B. Girshick
- Ilya Sutskever
Who trusts Atul Prakash overall
Papers from Atul Prakash's perspective
Ordered by how strongly the researchers Atul Prakash trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Learning Multiple Layers of Features from Tiny Images
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Robust Physical-World Attacks on Deep Learning Visual Classification (2018) — 2,198 citations
- Robust Physical-World Attacks on Deep Learning Models (2017) — 621 citations
- Analyzing the Interpretability Robustness of Self-Explaining Models (2019) — 7 citations
- Note on Attacking Object Detectors with Adversarial Stickers (2017) — 37 citations
- Physical Adversarial Examples for Object Detectors (2018) — 554 citations
- Robust Physical-World Attacks on Machine Learning Models (2017) — 343 citations
- IFTTT vs. Zapier: A Comparative Study of Trigger-Action Programming Frameworks (2017) — 37 citations
- ContexloT: Towards Providing Contextual Integrity to Appified IoT Platforms (2017) — 330 citations
- FlowFence: Practical Data Protection for Emerging IoT Application Frameworks (2016) — 298 citations
- Security Analysis of Emerging Smart Home Applications (2016) — 697 citations