Exploring the Impacts of Land Use/Cover Change on Ecosystem Services in Multiple Scenarios --The Case of Sichuan-Chongqing Region, China

no code implementations • 19 Dec 2023 • Ran Chen, Jing Zhao, Xiaomin Luo, Xinxue Yan, Xi Zheng, Yijun Mao, Xiaoping Fu, Xueqi Yao, Sijia Jiang

This study focuses on the "ecology-food" imbalance problem. taking Sichuan-Chongqing Region as an example, to set up future scenarios topredicate the distribution of ESs.

Multiface: A Dataset for Neural Face Rendering

1 code implementation • 22 Jul 2022 • Cheng-hsin Wuu, Ningyuan Zheng, Scott Ardisson, Rohan Bali, Danielle Belko, Eric Brockmeyer, Lucas Evans, Timothy Godisart, Hyowon Ha, Xuhua Huang, Alexander Hypes, Taylor Koska, Steven Krenn, Stephen Lombardi, Xiaomin Luo, Kevyn McPhail, Laura Millerschoen, Michal Perdoch, Mark Pitts, Alexander Richard, Jason Saragih, Junko Saragih, Takaaki Shiratori, Tomas Simon, Matt Stewart, Autumn Trimble, Xinshuo Weng, David Whitewolf, Chenglei Wu, Shoou-I Yu, Yaser Sheikh

Along with the release of the dataset, we conduct ablation studies on the influence of different model architectures toward the model's interpolation capacity of novel viewpoint and expressions.

Novel View Synthesis

TransformerCPI: improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments

2 code implementations • Bioinformatics 2020 • Lifan Chen, Xiaoqin Tan, Dingyan Wang, Feisheng Zhong, Xiaohong Liu, Tianbiao Yang, Xiaomin Luo, Kaixian Chen, Hualiang Jiang, Mingyue Zheng

Motivation Identifying compound–protein interaction (CPI) is a crucial task in drug discovery and chemogenomics studies, and proteins without three-dimensional structure account for a large part of potential biological targets, which requires developing methods using only protein sequence information to predict CPI.

Drug Discovery