107 citations · 131 across the 11 of their papers we have counts for
9 papers
CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery
Yuxiao Cheng, Ziqian Wang, Tingxiong Xiao +3
Time-series causal discovery (TSCD) is a fundamental problem of machine learning. However, existing synthetic datasets cannot properly evaluate or predict the algorithms' performan…
HAvatar: High-fidelity Head Avatar via Facial Model Conditioned Neural Radiance Field
Xiaochen Zhao, Lizhen Wang, Jingxiang Sun +3
The problem of modeling an animatable 3D human head avatar under light-weight setups is of significant importance but has not been well solved. Existing 3D representations either p…
HOPE: High-order Polynomial Expansion of Black-box Neural Networks
Tingxiong Xiao, Weihang Zhang, Yuxiao Cheng +1
Despite their remarkable performance, deep neural networks remain mostly ``black boxes'', suggesting inexplicability and hindering their wide applications in fields requiring makin…
SHoP: A Deep Learning Framework for Solving High-order Partial Differential Equations
Tingxiong Xiao, Runzhao Yang, Yuxiao Cheng +2
Solving partial differential equations (PDEs) has been a fundamental problem in computational science and of wide applications for both scientific and engineering research. Due to…
CUTS: Neural Causal Discovery from Irregular Time-Series Data
Yuxiao Cheng, Runzhao Yang, Tingxiong Xiao +4
Causal discovery from time-series data has been a central task in machine learning. Recently, Granger causality inference is gaining momentum due to its good explainability and hig…
DarkVision: A Benchmark for Low-light Image/Video Perception
Bo Zhang, Yuchen Guo, Runzhao Yang +4
Imaging and perception in photon-limited scenarios is necessary for various applications, e.g., night surveillance or photography, high-speed photography, and autonomous driving. I…