Yanbin Liu

According to our database, Yanbin Liu authored at least 33 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Ideological Isolation in Online Social Networks: A Survey of Computational Definitions, Metrics, and Mitigation Strategies.

Xiaodan Wang, Yanbin Liu, Shiqing Wu, Ziying Zhao, Yuxuan Hu, Weihua Li, Quan Bai

CoRR, January, 2026

Compression-Oriented Video Super-Resolution.

Shuyun Wang, Yanbin Liu, Ming Lu, Zhuojie Wu, Senmao Tian, Yandong Guo, Xin Yu

IEEE Trans. Image Process., 2026

2025

Reprogramming Vision Foundation Models for Spatio-Temporal Forecasting.

Changlu Chen, Yanbin Liu, Chaoxi Niu, Ling Chen, Tianqing Zhu

CoRR, July, 2025

Towards Superior Quantization Accuracy: A Layer-sensitive Approach.

Feng Zhang, Yanbin Liu, Weihua Li, Jie Lv, Xiaodan Wang, Quan Bai

CoRR, March, 2025

Tunnel Vision in Online Discourse: Formalization and Entropy-Based Quantification with LLM-Simulated Agents.

Xiaodan Wang, Yanbin Liu, Weihua Li, Quan Bai

Proceedings of the PRICAI 2025: Trends in Artificial Intelligence, 2025

2024

Bilaterally Normalized Scale-Consistent Sinkhorn Distance for Few-Shot Image Classification.

Yanbin Liu, Linchao Zhu, Xiaohan Wang, Makoto Yamada, Yi Yang

IEEE Trans. Neural Networks Learn. Syst., August, 2024

3D Brain and Heart Volume Generative Models: A Survey.

Yanbin Liu, Girish Dwivedi, Farid Boussaïd, Mohammed Bennamoun

ACM Comput. Surv., June, 2024

NeRFEditor: Differentiable Style Decomposition for 3D Scene Editing.

Chunyi Sun, Yanbin Liu, Junlin Han, Stephen Gould

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Test-Time Training for Spatial-Temporal Forecasting.

Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang

Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Multivariate Traffic Demand Prediction via 2D Spectral Learning and Global Spatial Optimization.

Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

TPR: Topology-Preserving Reservoirs for Generalized Zero-Shot Learning.

Hui Chen, Yanbin Liu, Yongqiang Ma, Nanning Zheng, Xin Yu

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

CRA-Eformer: Cross-Scale Residual Attention-Based Edge-Guide Transformer for Low-Dose CT Denoising.

Tong Wu, Yanbin Liu, Sira Yongchareon

Proceedings of the Neural Information Processing - 31st International Conference, 2024

Unsupervised Dense Prediction Using Differentiable Normalized Cuts.

Yanbin Liu, Stephen Gould

Proceedings of the Computer Vision - ECCV 2024, 2024

Class-Aware Sample Weight Learning for Cross-Modal Unsupervised Domain Adaptation in Cross-User Wearable Human Activity Recognition.

Tong Wu, Yanbin Liu, Sira Yongchareon

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

Bidirectional Spatial-Temporal Adaptive Transformer for Urban Traffic Flow Forecasting.

Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang

IEEE Trans. Neural Networks Learn. Syst., October, 2023

Inflating 2D convolution weights for efficient generation of 3D medical images.

Yanbin Liu, Girish Dwivedi, Farid Boussaïd, Frank M. Sanfilippo, Makoto Yamada, Mohammed Bennamoun

Comput. Methods Programs Biomed., October, 2023

Multitask Deep Learning for Accurate Risk Stratification and Prediction of Next Steps for Coronary CT Angiography Patients.

Juan Lu, Mohammed Bennamoun, Jonathon Stewart, Jason Kamran Eshraghian, Yanbin Liu, Benjamin J. W. Chow, Frank M. Sanfilippo, Girish Dwivedi

CoRR, 2023

Towards Understanding Gradient Approximation in Equality Constrained Deep Declarative Networks.

Stephen Gould, Ming Xu, Zhiwei Xu, Yanbin Liu

CoRR, 2023

RiskContra: A Contrastive Approach to Forecast Traffic Risks with Multi-Kernel Networks.

Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Spatial Bottleneck Transformer for Cellular Traffic Prediction in the Urban City.

Hexuan Weng, Yanbin Liu, Ling Chen

Proceedings of the AI 2023: Advances in Artificial Intelligence, 2023

2022

Feature-Robust Optimal Transport for High-Dimensional Data.

Mathis Petrovich, Chao Liang, Ryoma Sato, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection.

Shaoshen Wang, Yanbin Liu, Ling Chen, Chengqi Zhang

Proceedings of the International Joint Conference on Neural Networks, 2022

2021

LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport.

Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Cross-aligned and Gumbel-refactored Autoencoders for Multi-view Anomaly Detection.

Shaoshen Wang, Yanbin Liu, Ling Chen, Chengqi Zhang

Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

A Multi-Mode Modulator for Multi-Domain Few-Shot Classification.

Yanbin Liu, Juho Lee, Linchao Zhu, Ling Chen, Humphrey Shi, Yi Yang

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Feature Robust Optimal Transport for High-dimensional Data.

Mathis Petrovich, Chao Liang, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada

CoRR, 2020

Semantic Correspondence as an Optimal Transport Problem.

Yanbin Liu, Linchao Zhu, Makoto Yamada, Yi Yang

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

LSMI-Sinkhorn: Semi-supervised Squared-Loss Mutual Information Estimation with Optimal Transport.

Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang

CoRR, 2019

Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning.

Yanbin Liu, Juho Lee, Minseop Park, Saehoon Kim, Eunho Yang, Sung Ju Hwang, Yi Yang

Proceedings of the 7th International Conference on Learning Representations, 2019

Adaptive Sparse Confidence-Weighted Learning for Online Feature Selection.

Yanbin Liu, Yan Yan, Ling Chen, Yahong Han, Yi Yang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Transductive Propagation Network for Few-shot Learning.

Yanbin Liu, Juho Lee, Minseop Park, Saehoon Kim, Yi Yang

CoRR, 2018

Activities in Extended Video.

Fan Ma, Peike Li, Linchao Zhu, Xuanyi Dong, Yanbin Liu, Yi Yang

Proceedings of the 2018 TREC Video Retrieval Evaluation, 2018

2017

UTS submission to Google YouTube-8M Challenge 2017.

Linchao Zhu, Yanbin Liu, Yi Yang

CoRR, 2017