1. Yinghua Yao, Yuangang Pan, and Xixian Chen. Generative Co-Design of Antibody Sequences and Structures via Black-Box Guidance in a Shared Latent Space. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2025.
2. Yuanyuan Chang, Yinghua Yao*, Tao Qin, Mengmeng Wang, Ivor Tsang, and Guang Dai, Instructing Text-to-Image Diffusion Models via Classifier-Guided Semantic Optimisation. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2025.
3. Zhiqiang Zhong, Yinghua Yao, Davide Mottin, and Jun Pang. EVOL3D: A Large-Scale 3D Structure Dataset for Investigating Mutational Effects in Homologous Proteins. Proceedings of the AI4X International Conference, 2025.
4. Yinghua Yao, Yuangang Pan, Jing Li, Ivor Tsang, and Xin Yao. Generative Adversarial Ranking Nets. Journal of Machine Learning Research, vol. 25, no. 119, pp. 1–35, 2024.
5. Jing Li, Yuangang Pan, Yueming Lyu, Yinghua Yao, Yulei Sui, and Ivor W. Tsang. Earning Extra Performance from Restrictive Feedbacks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2023.
6. Yunce Zhao, Dashan Gao, Yinghua Yao, Zeqi Zhang, Bifei Mao and Xin Yao. Robust Deep Learning Models Against Semantic-Preserving Adversarial Attack. International Joint Conference on Neural Networks. 2023.
7. Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao: Differential-Critic GAN: Generating What You Want by a Cue of Preferences. IEEE Transactions on Neural Networks and Learning Systems. 2022.
8. Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao: Support Matching: A Novel Regularisation to Escape from Mode Collapse in GANs. In Proceedings of International Conference on Neural Information Processing, 40-48. 2019.
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