Shiqi Wang
Artificial Intelligence · with Jana · 2017–2022
A researcher in the Science corpus: 7 papers; trusts 99 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 179 citations into it; #25,672 of 35,345 by trust here, #10,942 by citations
- Safety, Robustness & Interpretability — 115 citations into it; #1,663 of 2,251 by trust here, #1,437 by citations
- Computer Vision and Pattern Recognition — 59 citations into it
- Signal Processing — 32 citations into it; #7,519 of 7,572 by trust here, #2,816 by citations
- Software — 31 citations into it; #1,207 of 1,227 by trust here, #602 by citations
- Program Analysis & Verification — 26 citations into it; #179 of 301 by trust here, #84 by citations
- Electrical and Electronic Engineering — 19 citations into it
- Hardware and Architecture — 15 citations into it
Whom Shiqi Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Ian J. Goodfellow
- Diederik P. Kingma
- Yann LeCun
- Geoffrey E. Hinton
- Christian Szegedy
- Yoshua Bengio
- Nicholas Carlini
- Kaiming He
- Ilya Sutskever
Who trusts Shiqi Wang overall
- Huan Zhang
- Hadi Salman
- Changliu Liu
- Kaidi Xu
- Hongge Chen
- Cho-Jui Hsieh
- Greg Yang
- Gagandeep Singh
- Suman Sekhar Jana
- Sven Gowal
Papers from Shiqi Wang's perspective
Ordered by how strongly the researchers Shiqi Wang 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)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Multi-lingual Evaluation of Code Generation Models (2022) — 247 citations
- Formal Security Analysis of Neural Networks using Symbolic Intervals (2018) — 532 citations
- Efficient Formal Safety Analysis of Neural Networks (2018) — 458 citations
- ReCode: Robustness Evaluation of Code Generation Models (2022) — 161 citations
- Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification (2021) — 332 citations
- MixTrain: Scalable Training of Formally Robust Neural Networks (2018) — 88 citations
- ContexloT: Towards Providing Contextual Integrity to Appified IoT Platforms (2017) — 330 citations