no code implementations • 1 May 2023 • Zhao Xu, Yaochen Xie, Youzhi Luo, Xuan Zhang, Xinyi Xu, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji
Here, we propose a novel deep learning framework to predict 3D geometries from molecular graphs.
1 code implementation • 1 Dec 2022 • Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Kian Hsiang Low
We observe that the fairness guarantees of exact SVs are too restrictive for SV estimates.
1 code implementation • 16 May 2022 • Lucas Agussurja, Xinyi Xu, Bryan Kian Hsiang Low
We show that for any two players, under some regularity conditions, their difference in Shapley value converges in probability to the difference in Shapley value of a limiting game whose characteristic function is proportional to the log-determinant of the joint Fisher information.
1 code implementation • 12 May 2022 • Wen Shi, Haoan Xu, Cong Sun, Jiwei Sun, Yamin Li, Xinyi Xu, Tianshu Zheng, Yi Zhang, Guangbin Wang, Dan Wu
Multi-slice magnetic resonance images of the fetal brain are usually contaminated by severe and arbitrary fetal and maternal motion.
no code implementations • 20 Apr 2022 • Kelly Payette, Hongwei Li, Priscille de Dumast, Roxane Licandro, Hui Ji, Md Mahfuzur Rahman Siddiquee, Daguang Xu, Andriy Myronenko, Hao liu, Yuchen Pei, Lisheng Wang, Ying Peng, Juanying Xie, Huiquan Zhang, Guiming Dong, Hao Fu, Guotai Wang, ZunHyan Rieu, Donghyeon Kim, Hyun Gi Kim, Davood Karimi, Ali Gholipour, Helena R. Torres, Bruno Oliveira, João L. Vilaça, Yang Lin, Netanell Avisdris, Ori Ben-Zvi, Dafna Ben Bashat, Lucas Fidon, Michael Aertsen, Tom Vercauteren, Daniel Sobotka, Georg Langs, Mireia Alenyà, Maria Inmaculada Villanueva, Oscar Camara, Bella Specktor Fadida, Leo Joskowicz, Liao Weibin, Lv Yi, Li Xuesong, Moona Mazher, Abdul Qayyum, Domenec Puig, Hamza Kebiri, Zelin Zhang, Xinyi Xu, Dan Wu, Kuanlun Liao, Yixuan Wu, Jintai Chen, Yunzhi Xu, Li Zhao, Lana Vasung, Bjoern Menze, Meritxell Bach Cuadra, Andras Jakab
Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context.
1 code implementation • 17 Dec 2021 • Sebastian Shenghong Tay, Xinyi Xu, Chuan Sheng Foo, Bryan Kian Hsiang Low
This paper presents a novel collaborative generative modeling (CGM) framework that incentivizes collaboration among self-interested parties to contribute data to a pool for training a generative model (e. g., GAN), from which synthetic data are drawn and distributed to the parties as rewards commensurate to their contributions.
no code implementations • NeurIPS 2021 • Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, Bryan Kian Hsiang Low
In this paper, we adopt federated learning as a gradient-based formalization of collaborative machine learning, propose a novel cosine gradient Shapley value to evaluate the agents’ uploaded model parameter updates/gradients, and design theoretically guaranteed fair rewards in the form of better model performance.
no code implementations • NeurIPS 2021 • Xinyi Xu, Zhaoxuan Wu, Chuan Sheng Foo, Bryan Kian Hsiang Low
We observe that the diversity of the data points is an inherent property of the dataset that is independent of validation.
3 code implementations • 30 Sep 2021 • Zhao Xu, Youzhi Luo, Xuan Zhang, Xinyi Xu, Yaochen Xie, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji
Here, we propose to predict the ground-state 3D geometries from molecular graphs using machine learning methods.
Ranked #1 on 3D Geometry Prediction on Molecule3D val
no code implementations • 20 Jul 2021 • Xinyi Xu, Cheng Deng, Yaochen Xie, Shuiwang Ji
Our framework embeds the given graph into multiple subspaces, of which each representation is prompted to encode specific characteristics of graphs.
2 code implementations • 20 Nov 2020 • Xinyi Xu, Lingjuan Lyu
In this paper, we propose a novel Robust and Fair Federated Learning (RFFL) framework to achieve collaborative fairness and adversarial robustness simultaneously via a reputation mechanism.
1 code implementation • 17 Nov 2020 • Xinyi Xu, Zhengyang Wang, Cheng Deng, Hao Yuan, Shuiwang Ji
Grouping has been commonly used in deep metric learning for computing diverse features.
no code implementations • 2 Nov 2020 • Abhinav Sharma, Advait Deshpande, Yanming Wang, Xinyi Xu, Prashan Madumal, Anbin Hou
We propose a novel non-randomized anytime orienteering algorithm for finding k-optimal goals that maximize reward on a specialized graph with budget constraints.
1 code implementation • 27 Aug 2020 • Lingjuan Lyu, Xinyi Xu, Qian Wang
In current deep learning paradigms, local training or the Standalone framework tends to result in overfitting and thus poor generalizability.
no code implementations • 8 Aug 2020 • Xinyi Xu, Tiancheng Huang, Pengfei Wei, Akshay Narayan, Tze-Yun Leong
This work is inspired by recent advances in hierarchical reinforcement learning (HRL) (Barto and Mahadevan 2003; Hengst 2010), and improvements in learning efficiency from heuristic-based subgoal selection, experience replay (Lin 1993; Andrychowicz et al. 2017), and task-based curriculum learning (Bengio et al. 2009; Zaremba and Sutskever 2014).
no code implementations • CVPR 2019 • Xinyi Xu, Yanhua Yang, Cheng Deng, Feng Zheng
The asymmetric structure enables the two data streams to interlace each other, which allows for the informative comparison between new data pairs over iterations.