Weijia Zhang

According to our database, Weijia Zhang authored at least 21 papers between 2014 and 2024.

Collaborative distances:

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

2024

Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees.

Weijia Zhang, Chun Kai Ling, Xuanhui Zhang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Rethinking the Value of Labels for Instance-Dependent Label Noise Learning.

Hanwen Deng, Weijia Zhang, Min-Ling Zhang

CoRR, 2023

Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection.

Zhaofei Wang, Weijia Zhang, Min-Ling Zhang

CoRR, 2023

Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning.

Wei Tang, Weijia Zhang, Min-Ling Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Local Low-Rank Approximation With Superpixel-Guided Locality Preserving Graph for Hyperspectral Image Classification.

Shujun Yang, Yu Zhang, Yuheng Jia, Weijia Zhang

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022

Imbalanced volunteer engagement in cultural heritage crowdsourcing: a task-related exploration based on causal inference.

Xuanhui Zhang, Weijia Zhang, Yuxiang (Chris) Zhao, Qinghua Zhu

Inf. Process. Manag., 2022

A Unified Survey of Treatment Effect Heterogeneity Modelling and Uplift Modelling.

Weijia Zhang, Jiuyong Li, Lin Liu

ACM Comput. Surv., 2022

Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision.

Wei Tang, Weijia Zhang, Min-Ling Zhang

CoRR, 2022

Towards Learning Causal Representations from Multi-Instance Bags.

Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang

CoRR, 2022

Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization.

Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

A general framework for causal classification.

Jiuyong Li, Weijia Zhang, Lin Liu, Kui Yu, Thuc Duy Le, Jixue Liu

Int. J. Data Sci. Anal., 2021

Non-I.I.D. Multi-Instance Learning for Predicting Instance and Bag Labels with Variational Auto-Encoder.

Weijia Zhang

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Treatment Effect Estimation with Disentangled Latent Factors.

Weijia Zhang, Lin Liu, Jiuyong Li

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

A unified survey on treatment effect heterogeneity modeling and uplift modeling.

Weijia Zhang, Jiuyong Li, Lin Liu

CoRR, 2020

MONET: a toolbox integrating top-performing methods for network modularization.

Mattia Tomasoni, Sergio Gómez, Jake Crawford, Weijia Zhang, Sarvenaz Choobdar, Daniel Marbach, Sven Bergmann

Bioinform., 2020

Robust Multi-Instance Learning with Stable Instances.

Weijia Zhang, Lin Liu, Jiuyong Li

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019

Distributionally Robust Multi-instance Learning with Stable Instances.

Weijia Zhang, Jiuyong Li, Lin Liu

CoRR, 2019

2018

Estimating heterogeneous treatment effect by balancing heterogeneity and fitness.

Weijia Zhang, Thuc Duy Le, Lin Liu, Jiuyong Li

BMC Bioinform., 2018

miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase.

Taosheng Xu, Ning Su, Lin Liu, Junpeng Zhang, Hongqiang Wang, Weijia Zhang, Jie Gui, Kui Yu, Jiuyong Li, Thuc Duy Le

BMC Bioinform., 2018

2017

Mining heterogeneous causal effects for personalized cancer treatment.

Weijia Zhang, Thuc Duy Le, Lin Liu, Zhi-Hua Zhou, Jiuyong Li

Bioinform., 2017

2014

Multi-Instance Learning with Distribution Change.

Weijia Zhang, Zhi-Hua Zhou

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014