Yao Qin
Yao Qin
Assistant Professor at UCSB & Senior Research Scientist at Google
Verified email at - Homepage
Cited by
Cited by
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction
Y Qin, D Song, H Chen, W Cheng, G Jiang, G Cottrell
International Joint Conference on Artificial Intelligence (IJCAI), 2017, 2017
Saliency Detection via Cellular Automata
Y Qin, H Lu, Y Xu, H Wang
Computer Vision and Pattern Recognition (CVPR), 2015, 110-119, 2015
Imperceptible, Robust and Targeted Adversarial Examples for Automatic Speech Recognition
Y Qin, N Carlini, I Goodfellow, G Cottrell, C Raffel
International Conference on Machine Learning (ICML), 2019., 2019
Autofocus Layer for Semantic Segmentation
Y Qin, K Kamnitsas, S Ancha, J Nanavati, G Cottrell, A Criminisi, A Nori
International Conference on Medical Image Computing and Computer Assisted …, 2018
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions
Y Qin*, N Frosst*, S Sabour, C Raffel, G Cottrell, G Hinton
International Conference on Learning Representations (ICLR), 2020, 2020
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation
T Wang, X Wang, Y Qin, B Packer, K Li, J Chen, A Beutel, E Chi
EMNLP 2020, 2020
Hierarchical Cellular Automata for Visual Saliency
Y Qin, M Feng, H Lu, GW Cottrell
International Journal of Computer Vision (IJCV), 2018, 2018
Are Vision Transformers Robust to Patch Perturbations?
J Gu, V Tresp, Y Qin
European Conference on Computer Vision (ECCV), 2022, 2022
Improving Calibration through the Relationship with Adversarial Robustness
Y Qin, X Wang, A Beutel, EH Chi
Neural Information Processing Systems (NeurIPS), 2021, 2021
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation
Y Qin, C Zhang, T Chen, B Lakshminarayanan, A Beutel, X Wang
Neural Information Processing Systems (NeurIPS), 2022, 2022
Deflecting Adversarial Attacks
Y Qin, N Frosst, C Raffel, G Cottrell, G Hinton
A systematic survey of prompt engineering on vision-language foundation models
J Gu, Z Han, S Chen, A Beirami, B He, G Zhang, R Liao, Y Qin, V Tresp, ...
arXiv preprint arXiv:2307.12980, 2023
Evaluation Methodology for Attacks against Confidence Thresholding Models
I Goodfellow, Y Qin, D Berthelot
Opinion Evolution in Open Community
Q Pan, Y Qin, Y Xu, M Tong, M He
International Journal of Modern Physics C 28 (01), 1750003, 2017
Towards Robust Prompts on Vision-Language Models
J Gu, A Beirami, X Wang, A Beutel, P Torr, Y Qin
arXiv preprint arXiv:2304.08479, 2023
Training Deep Boltzmann Networks with Sparse Ising Machines
S Niazi, NA Aadit, M Mohseni, S Chowdhury, Y Qin, KY Camsari
arXiv preprint arXiv:2303.10728, 2023
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data
Z Shi, N Carlini, A Balashankar, L Schmidt, CJ Hsieh, A Beutel, Y Qin
Neural Information Processing Systems (NeurIPS), 2023, 2023
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel
Y Qin, X Wang, B Lakshminarayanan, EH Chi, A Beutel
IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 2023
Dual stage attention based recurrent neural network for time series prediction
D Song, H Chen, G Jiang, Y Qin
US Patent 10,929,674, 2021
Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting
X Zhang, S Li, X Yang, C Tian, Y Qin, LR Petzold
arXiv preprint arXiv:2305.12723, 2023
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