Publications (11)
Synergizing Deconfounding and Temporal Generalization For Time-series Counterfactual Outcome Estimation
Yiling Liu, Juncheng Dong, Chen Fu +4
Estimating counterfactual outcomes from time-series observations is crucial for effective decision-making, e.g. when to administer a life-saving treatment, yet remains significantl…
Estimating Causal Effects using a Multi-task Deep Ensemble
Ziyang Jiang, Zhuoran Hou, Yiling Liu +3
A number of methods have been proposed for causal effect estimation, yet few have demonstrated efficacy in handling data with complex structures, such as images. To fill this gap,…
Causal Mediation Analysis with Multi-dimensional and Indirectly Observed Mediators
Ziyang Jiang, Yiling Liu, Michael H. Klein +5
Causal mediation analysis (CMA) is a powerful method to dissect the total effect of a treatment into direct and mediated effects within the potential outcome framework. This is imp…
Domain Adaptation via Rebalanced Sub-domain Alignment
Yiling Liu, Juncheng Dong, Ziyang Jiang +5
Unsupervised domain adaptation (UDA) is a technique used to transfer knowledge from a labeled source domain to a different but related unlabeled target domain. While many UDA metho…
Personalized Transcranial Electrical Stimulation: A Review of Computational Modeling and Optimization
Mo Wang, Kexin Zheng, Yingyue Xin +8
Objective. Personalized transcranial electrical stimulation (tES) has gained growing attention due to the substantial inter-individual variability in brain anatomy and physiology.…
UnPuzzle: A Unified Framework for Pathology Image Analysis
Dankai Liao, Sicheng Chen, Nuwa Xi +10
Pathology image analysis plays a pivotal role in medical diagnosis, with deep learning techniques significantly advancing diagnostic accuracy and research. While numerous studies h…
Deep Causal Inference for Point-referenced Spatial Data with Continuous Treatments
Ziyang Jiang, Zach Calhoun, Yiling Liu +2
Causal reasoning is often challenging with spatial data, particularly when handling high-dimensional inputs. To address this, we propose a neural network (NN) based framework integ…
CARE: Turning LLMs Into Causal Reasoning Expert
Juncheng Dong, Yiling Liu, Ahmed Aloui +2
Large language models (LLMs) have recently demonstrated impressive capabilities across a range of reasoning and generation tasks. However, research studies have shown that LLMs lac…
Unsupervised Learning of Monocular Depth and Ego-Motion Using Multiple Masks
Guangming Wang, Hesheng Wang, Yiling Liu +1
A new unsupervised learning method of depth and ego-motion using multiple masks from monocular video is proposed in this paper. The depth estimation network and the ego-motion esti…
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel
Ziyang Jiang, Tongshu Zheng, Yiling Liu +1
It is challenging to guide neural network (NN) learning with prior knowledge. In contrast, many known properties, such as spatial smoothness or seasonality, are straightforward to…
IFR-Net: Iterative Feature Refinement Network for Compressed Sensing MRI
Yiling Liu, Qiegen Liu, Minghui Zhang +3
To improve the compressive sensing MRI (CS-MRI) approaches in terms of fine structure loss under high acceleration factors, we have proposed an iterative feature refinement model (…