Bita Darvish Rouhani
Artificial Intelligence · 2017–2019
A researcher in the Science corpus: 6 papers; trusts 156 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 97 citations into it; #9,562 of 35,345 by trust here, #10,430 by citations
- Computer Vision and Pattern Recognition — 66 citations into it; #11,564 of 21,575 by trust here, #18,266 by citations
- Safety, Robustness & Interpretability — 42 citations into it; #923 of 2,251 by trust here, #1,162 by citations
- Signal Processing — 32 citations into it
- Privacy & Security — 12 citations into it; #331 of 709 by trust here, #361 by citations
- Computer Networks and Communications — 11 citations into it
- Efficiency & Compression — 10 citations into it
- Model Architectures — 10 citations into it
Whom Bita Darvish Rouhani trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Yann LeCun
- Geoffrey E. Hinton
- Yoshua Bengio
- Jia Deng
- Ilya Sutskever
- Ian J. Goodfellow
- Nicolas Papernot
- Nicholas Carlini
- Christian Szegedy
Who trusts Bita Darvish Rouhani overall
- M. Sadegh Riazi
- Mingfu Xue
- Jiasi Chen
- Abhishek Chakraborty
- Ehsan Hesamifard
- Ali Shahin Shamsabadi
- Chiraag Shashikant Juvekar
- Sameer Wagh
- Amartya Sanyal
- Eleftheria Makri
Papers from Bita Darvish Rouhani's perspective
Ordered by how strongly the researchers Bita Darvish Rouhani 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- DeepAttest: An End-to-End Attestation Framework for Deep Neural Networks (2019) — 82 citations
- DeepSecure: Scalable Provably-Secure Deep Learning (2017) — 452 citations
- DeepSigns: An End-to-End Watermarking Framework for Ownership Protection of Deep Neural Networks (2019) — 331 citations
- Serving DNNs in Real Time at Datacenter Scale with Project Brainwave (2018) — 325 citations
- BlackMarks: Blackbox Multibit Watermarking for Deep Neural Networks (2018) — 64 citations
- DeepFense: Online Accelerated Defense Against Adversarial Deep Learning (2017) — 50 citations