Incomplete markets, Knightian uncertainty and high-water marks. - Fengjun Liu; Yingjie Niu; Zhentao Zou (Oper. Res. Lett., 2020)

TsFeX: Contact Tracing Model using Time Series Feature Extraction and Gradient Boosting. - Manuela Nayantara Jeyaraj; Valerio Antonini; Yingjie Niu; Sonal Santosh Baberwal; Faithful Chiagoziem Onwuegbuche; Robert Foskin (CoRR, 2021)

Auditory and visual warning information generation of the risk object in driving scenes based on weakly supervised learning. - Yingjie Niu; Ming Ding 002; Yuxiao Zhang; Kento Ohtani; Kazuya Takeda (IV, 2022)

Learning to Generalize for Cross-domain QA. - Yingjie Niu; Linyi Yang; Ruihai Dong; Yue Zhang 004 (ACL (Findings), 2023)

Open-world driving scene segmentation via multi-stage and multi-modality fusion of vision-language embedding. - Yingjie Niu; Ming Ding 002; Yuxiao Zhang; Maoning Ge; Hanting Yang; Kazuya Takeda (IV, 2023)

Synthesizing Realistic Snow Effects in Driving Images Using GANs and Real Data with Semantic Guidance. - Hanting Yang; Ming Ding 002; Alexander Carballo; Yuxiao Zhang; Kento Ohtani; Yingjie Niu; Maoning Ge; Yan Feng; Kazuya Takeda (IV, 2023)

LiDAR Point Cloud Translation Between Snow and Clear Conditions Using Depth Images and GANs. - Yuxiao Zhang; Ming Ding 002; Hanting Yang; Yingjie Niu; Yan Feng; Maoning Ge; Alexander Carballo; Kazuya Takeda (IV, 2023)

R-Cut: Enhancing Explainability in Vision Transformers with Relationship Weighted Out and Cut. - Yingjie Niu; Ming Ding 002; Maoning Ge; Robin Karlsson; Yuxiao Zhang; Kazuya Takeda (CoRR, 2023)

DRUformer: Enhancing the driving scene Important object detection with driving relationship self-understanding. - Yingjie Niu; Ming Ding 002; Keisuke Fujii 001; Kento Ohtani; Alexander Carballo; Kazuya Takeda (CoRR, 2023)

L-DIG: A GAN-Based Method for LiDAR Point Cloud Processing under Snow Driving Conditions. - Yuxiao Zhang; Ming Ding 002; Hanting Yang; Yingjie Niu; Yan Feng; Kento Ohtani; Kazuya Takeda (Sensors, 2023)

Evaluating Financial Relational Graphs: Interpretation Before Prediction. - Yingjie Niu; Lanxin Lu; Rian Dolphin; Valerio Potì; Ruihai Dong (ICAIF, 2024)

Contrasting Disentangled Partial Observations for Pedestrian Action Prediction. - Yan Feng; Alexander Carballo; Yingjie Niu; Kazuya Takeda (IV, 2024)

DRUformer: Enhancing Driving Scene Important Object Detection With Driving Scene Relationship Understanding. - Yingjie Niu; Ming Ding 002; Keisuke Fujii 001; Kento Ohtani; Alexander Carballo; Kazuya Takeda (IEEE Access, 2024)

Robust dynamic contracts with multiple agents. - Yingjie Niu; Zhentao Zou (Games Econ. Behav., 2024)

Disaster learning and aggregate investment. - Yingjie Niu; Jinqiang Yang; Zhentao Zou (J. Econ. Theory, 2024)

R-Cut: Enhancing Explainability in Vision Transformers with Relationship Weighted Out and Cut. - Yingjie Niu; Ming Ding 002; Maoning Ge; Robin Karlsson; Yuxiao Zhang; Alexander Carballo; Kazuya Takeda (Sensors, 2024)

LiDAR Point Cloud Augmentation for Adverse Conditions Using Conditional Generative Model. - Yuxiao Zhang; Ming Ding 002; Hanting Yang; Yingjie Niu; Maoning Ge; Kento Ohtani; Chi Zhang; Kazuya Takeda (Remote. Sens., 2024)

NGAT: A Node-level Graph Attention Network for Long-term Stock Prediction. - Yingjie Niu; Mingchuan Zhao; Valerio Potì; Ruihai Dong (CoRR, 2025)