Soroush Mehri
Artificial Intelligence · 2016–2021
A researcher in the Science corpus: 6 papers; trusts 196 researchers and is trusted by 29 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 130 citations into it
- Computer Vision and Pattern Recognition — 71 citations into it; #9,323 of 21,575 by trust here, #4,245 by citations
- Model Architectures — 46 citations into it
- Optimization & Training — 37 citations into it
- Safety, Robustness & Interpretability — 32 citations into it
- Representation & Self-Supervised Learning — 30 citations into it
- Natural Language Processing — 24 citations into it; #2,624 of 5,688 by trust here, #1,418 by citations
- Cognitive Neuroscience — 20 citations into it
Whom Soroush Mehri trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Alex Graves
- Diederik P. Kingma
- J. Urgen Schmidhuber
- Kaiming He
- Sepp Hochreiter
- Alex Krizhevsky
- Hugo Larochelle
- Ilya Sutskever
Who trusts Soroush Mehri overall
- Wei Ping
- Takuma Okamoto
- Chris Donahue
- Jan Skoglund
- Yang Ai
- Jean-Marc Valin
- Yaniv Taigman
- Xu Tan
- Lior Wolf
- Kainan Peng
Papers from Soroush Mehri's perspective
Ordered by how strongly the researchers Soroush Mehri 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- SampleRNN: An Unconditional End-to-End Neural Audio Generation Model (2016) — 630 citations
- Learning Rapid-Temporal Adaptations (2017) — 13 citations
- Deep Complex Networks (2017) — 1,046 citations
- Benchmarking Bias Mitigation Algorithms in Representation Learning through Fairness Metrics (2021) — 38 citations
- Rapid Adaptation with Conditionally Shifted Neurons (2017) — 325 citations
- Char2Wav: End-to-End Speech Synthesis (2017) — 460 citations