Weijia Zhang - RankMe

38 papers A* 9A 2Journal 27

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Calibratable Disambiguation Loss for Multi-Instance Partial-Label Learning. CoRR Wei Tang, Yin-Fang Yang, Weijia Zhang, Min-Ling Zhang
2025	J	`jnl`	Disentangled Representation Learning for Causal Inference With Instruments. IEEE Trans. Neural Networks Learn. Syst. Debo Cheng, Jiuyong Li, Lin Liu, Ziqi Xu, Weijia Zhang, Jixue Liu, Thuc Duy Le
2025	J	`jnl`	Instance-dependent label noise learning via separating style from content. Pattern Recognit. Lett. Han-Wen Deng, Weijia Zhang, Min-Ling Zhang
2025	J	`jnl`	Multi-Instance Partial-Label Learning with Margin Adjustment. CoRR Wei Tang, Yin-Fang Yang, Zhaofei Wang, Weijia Zhang, Min-Ling Zhang
2025	A*	`conf`	Partial Label Causal Representation Learning for Instance-Dependent Supervision and Domain Generalization. AAAI Yizhi Wang, Weijia Zhang, Min-Ling Zhang
2024	J	`jnl`	Attention Is Not What You Need: Revisiting Multi-Instance Learning for Whole Slide Image Classification. CoRR Xin Liu, Weijia Zhang, Min-Ling Zhang
2024	A*	`conf`	Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees. AAAI Weijia Zhang, Chun Kai Ling, Xuanhui Zhang
2024	J	`jnl`	Disentangled Representation Learning for Causal Inference with Instruments. CoRR Debo Cheng, Jiuyong Li, Lin Liu, Ziqi Xu, Weijia Zhang, Jixue Liu, Thuc Duy Le
2024	A*	`conf`	Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning. IJCAI Wei Tang, Weijia Zhang, Min-Ling Zhang
2024	J	`jnl`	Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning. CoRR Wei Tang, Weijia Zhang, Min-Ling Zhang
2024	J	`jnl`	HACSurv: A Hierarchical Copula-based Approach for Survival Analysis with Dependent Competing Risks. CoRR Xin Liu, Weijia Zhang, Min-Ling Zhang
2024	A*	`conf`	Multi-Instance Partial-Label Learning with Margin Adjustment. NeurIPS Wei Tang, Yin-Fang Yang, Zhaofei Wang, Weijia Zhang, Min-Ling Zhang
2024	J	`jnl`	Multi-instance partial-label learning: towards exploiting dual inexact supervision. Sci. China Inf. Sci. Wei Tang, Weijia Zhang, Min-Ling Zhang
2024	A	`conf`	Proposal Feature Learning Using Proposal Relations for Weakly Supervised Object Detection. ICME Zhaofei Wang, Weijia Zhang, Min-Ling Zhang
2023	J	`jnl`	Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees. CoRR Weijia Zhang, Chun Kai Ling, Xuanhui Zhang
2023	A*	`conf`	Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning. NeurIPS Wei Tang, Weijia Zhang, Min-Ling Zhang
2023	J	`jnl`	Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning. CoRR Wei Tang, Weijia Zhang, Min-Ling Zhang
2023	J	`jnl`	Rethinking the Value of Labels for Instance-Dependent Label Noise Learning. CoRR Hanwen Deng, Weijia Zhang, Min-Ling Zhang
2023	J	`jnl`	Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection. CoRR Zhaofei Wang, Weijia Zhang, Min-Ling Zhang
2022	J	`jnl`	A Unified Survey of Treatment Effect Heterogeneity Modelling and Uplift Modelling. ACM Comput. Surv. Weijia Zhang, Jiuyong Li, Lin Liu
2022	J	`jnl`	Imbalanced volunteer engagement in cultural heritage crowdsourcing: a task-related exploration based on causal inference. Inf. Process. Manag. Xuanhui Zhang, Weijia Zhang, Yuxiang (Chris) Zhao, Qinghua Zhu
2022	J	`jnl`	Local Low-Rank Approximation With Superpixel-Guided Locality Preserving Graph for Hyperspectral Image Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Shujun Yang, Yu Zhang, Yuheng Jia, Weijia Zhang
2022	A*	`conf`	Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization. NeurIPS Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang
2022	J	`jnl`	Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision. CoRR Wei Tang, Weijia Zhang, Min-Ling Zhang
2022	J	`jnl`	Towards Learning Causal Representations from Multi-Instance Bags. CoRR Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang
2021	J	`jnl`	A general framework for causal classification. Int. J. Data Sci. Anal. Jiuyong Li, Weijia Zhang, Lin Liu, Kui Yu, Thuc Duy Le, Jixue Liu
2021	A*	`conf`	Non-I.I.D. Multi-Instance Learning for Predicting Instance and Bag Labels with Variational Auto-Encoder. IJCAI Weijia Zhang
2021	A*	`conf`	Treatment Effect Estimation with Disentangled Latent Factors. AAAI Weijia Zhang, Lin Liu, Jiuyong Li
2020	J	`jnl`	A general framework for causal classification. CoRR Jiuyong Li, Weijia Zhang, Lin Liu, Kui Yu, Thuc Duy Le, Jixue Liu
2020	J	`jnl`	A unified survey on treatment effect heterogeneity modeling and uplift modeling. CoRR Weijia Zhang, Jiuyong Li, Lin Liu
2020	J	`jnl`	MONET: a toolbox integrating top-performing methods for network modularization. Bioinform. Mattia Tomasoni, Sergio Gómez, Jake Crawford, Weijia Zhang, Sarvenaz Choobdar, Daniel Marbach, Sven Bergmann
2020	A	`conf`	Robust Multi-Instance Learning with Stable Instances. ECAI Weijia Zhang, Lin Liu, Jiuyong Li
2020	J	`jnl`	Treatment effect estimation with disentangled latent factors. CoRR Weijia Zhang, Lin Liu, Jiuyong Li
2019	J	`jnl`	Distributionally Robust Multi-instance Learning with Stable Instances. CoRR Weijia Zhang, Jiuyong Li, Lin Liu
2018	J	`jnl`	Estimating heterogeneous treatment effect by balancing heterogeneity and fitness. BMC Bioinform. Weijia Zhang, Thuc Duy Le, Lin Liu, Jiuyong Li
2018	J	`jnl`	miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase. BMC Bioinform. Taosheng Xu, Ning Su, Lin Liu, Junpeng Zhang, Hongqiang Wang, Weijia Zhang, Jie Gui, Kui Yu, Jiuyong Li, Thuc Duy Le
2017	J	`jnl`	Mining heterogeneous causal effects for personalized cancer treatment. Bioinform. Weijia Zhang, Thuc Duy Le, Lin Liu, Zhi-Hua Zhou, Jiuyong Li
2014	A*	`conf`	Multi-Instance Learning with Distribution Change. AAAI Weijia Zhang, Zhi-Hua Zhou