Sahand Sharifzadeh
Artificial Intelligence · 2016–2025
A researcher in the Science corpus: 3 papers; trusts 9 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 128 citations into it; #25,330 of 35,345 by trust here, #27,551 by citations
- Computer Vision and Pattern Recognition — 114 citations into it
- Reinforcement Learning — 9 citations into it
Whom Sahand Sharifzadeh trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Andrew Y. Ng
- Ben J. A. Kröse
- Pieter Abbeel
- John N. Tsitsiklis
- Deepak Ramachandran
- Brian D. Ziebart
- Moritz Werling
- Volodymyr Mnih
- Stuart J. Russell
- Benjamin Van Roy
Who trusts Sahand Sharifzadeh overall
- Edouard Leurent
- Shansi Zhang
- Sen Wang
- Victor Talpaert
- Joel Janai
- B. R. Kiran
- Ibrahim Sobh
- Daoyuan Jia
- Fatma Güney
Papers from Sahand Sharifzadeh's perspective
Ordered by how strongly the researchers Sahand Sharifzadeh trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Human-level control through deep reinforcement learning
Their papers
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- Flamingo: a Visual Language Model for Few-Shot Learning (2022) — 6,220 citations
- Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks (2016) — 96 citations