Publications

Connor Clayton, Jiaqi Leng, Gengzhi Yang, Yi-Ling Qiao, Ming Lin, Xiaodi Wu (2024). Differentiable Quantum Computing for Large-scale Linear Control. NeurIPS 2024.

Shutong Zhang, Yi-Ling Qiao, Guanglei Zhu, Eric Heiden, Dylan Turpin, Jingzhou Liu, Ming Lin, Miles Macklin, Animesh Garg (2024). HandyPriors - Physically Consistent Perception of Hand-Object Interactions with Differentiable Priors. ICRA 2024.

Sanghyun Son, Laura Yu Zheng, Ryan Sullivan, Yi-Ling Qiao, Ming C. Lin (2023). Gradient Informed Proximal Policy Optimization. NeurIPS 2023.

Zhou Xian, Theophile Gervet, Zhenjia Xu, Yi-Ling Qiao, Tsun-Hsuan Wang, Yian Wang, Chen Wang, Katerina Fragkiadaki, David Held, Chris Atkeson, Josh Tenenbaum, Daniela Rus (2023). Towards Generalist Robots - Learning Paradigms for Scalable Skill Acquisition. CoRL 2023 Workshop Organizer.

Yi-Ling Qiao, Alexander Gao, Yiran Xu, Yue Feng, Jia-Bin Huang, Ming C. Lin (2023). Dynamic Mesh-Aware Radiance Fields. ICCV 2023.

Xuan Li, Yi-Ling Qiao, Peter Yichen Chen, Krishna Murthy Jatavallabhula, Ming Lin, Chenfanfu Jiang, Chuang Gan (2023). PAC-NeRF - Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification. ICLR 2023.

Jiaqi Leng1, Yuxiang Peng1, Yi-Ling Qiao1, Ming C. Lin, Xiaodi Wu (2022). Differentiable Analog Quantum Computing for Optimization and Control. NeurIPS 2022.

Sanghyun Son, Yi-Ling Qiao, Jason Sewall, Ming C. Lin (2022). Differentiable Hybrid Traffic Simulation. SIGGRAPH Asia 2022, Journal Track.

Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin (2021). Differentiable Simulation of Soft Multi-body Systems. Conference on Neural Information Processing Systems (NeurIPS 2021).

Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin (2021). Efficient Differentiable Simulation of Articulated Bodies. International Conference on Machine Learning (ICML 2021).

Jing Liang, Yi-Ling Qiao, Tianrui Guan, Dinesh Manocha (2021). OF-VO Efficient Navigation among Pedestrians Using Commodity Sensors. IEEE Robotics and Automation Letters (ICRA/RAL 2021).

Tetsuya Takahashi, Junbang Liang, Yi-Ling Qiao, Ming C. Lin (2021). Differentiable Fluids with Solid Coupling for Learning and Control. AAAI Conference on Artificial Intelligence (AAAI 2021).

Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin (2020). Scalable Differentiable Physics for Learning and Control. International Conference on Machine Learning (ICML 2020).

Yi-Ling Qiao, Lin Gao, Shu-Zhi Liu, Ligang Liu, Yu-Kun Lai, Xilin Chen (2020). Learning-based Intrinsic Reflectional Symmetry Detection. IEEE Transactions on Visualization and Computer Graphics.

Yi-Ling Qiao, Lin Gao, Jie Yang, Paul L. Rosin, Yu-Kun Lai, Xilin Chen (2020). Learning on 3D Meshes with Laplacian Encoding and Pooling. IEEE Transactions on Visualization and Computer Graphics.

Yi-Ling Qiao, Yu-Kun Lai, Hongbo Fu, Lin Gao (2019). Synthesizing Mesh Deformation Sequences with Bidirectional LSTM. IEEE Transactions on Visualization and Computer Graphics.

Yi-Ling Qiao, Chang Shi, Chenjian Wang, Hao Li, Matt Haberland, Xiyang Luo, Andrew M. Stuart, Andrea L. Bertozzi (2019). Uncertainty Quantification for Semi-supervised Multi-class Classification in Image Processing and Ego-Motion Analysis of Body-Worn Videos. Electronic Imaging 2019.

Lin Gao, Jie Yang, Yi-Ling Qiao, Yu-Kun Lai, Paul L. Rosin, Weiwei Xu, Shihong Xia (2018). Automatic Unpaired Shape Deformation Transfer. In SIGGRAPH Asia 2018.

Yi-Ling Qiao, Lin Gao, Yu-Kun Lai, Fang-Lue Zhang, Ming-Ze Yuan, Shihong Xia (2018). SF-Net Learning Scene Flow from RGB-D Images with CNNs. The British Machine Vision Conference (BMVC 2018).