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ORCIDWeijia Zhang 0001
Person information
- affiliation: University of Newcastle, School of Information and Physical Sciences, NSW, Australia
- affiliation (2021 - 2023): Southeast University, Nanjing, China
- affiliation (PhD 2018): University of South Australia, Australia
- affiliation (former): Nanjing University, China
Other persons with the same name
- Weijia Zhang — disambiguation page
- Weijia Zhang 0002 — MathWorks, Natick, MA, USA (and 1 more)
- Weijia Zhang 0003
![[0000-0001-5085-5216]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-5085-5216")
— Hong Kong University of Science and Technology (and 1 more) - Weijia Zhang 0004 — University of Amsterdam, The Netherlands
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2020 – today
- 2024
[j9]Wei Tang, Weijia Zhang, Min-Ling Zhang:
Multi-instance partial-label learning: towards exploiting dual inexact supervision. Sci. China Inf. Sci. 67(3) (2024)- [c9]Weijia Zhang, Chun Kai Ling, Xuanhui Zhang:
Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees. AAAI 2024: 20613-20621 - [c8]Zhaofei Wang, Weijia Zhang, Min-Ling Zhang:
Proposal Feature Learning Using Proposal Relations for Weakly Supervised Object Detection. ICME 2024: 1-6 - [c7]Wei Tang, Weijia Zhang, Min-Ling Zhang:
Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning. IJCAI 2024: 4973-4981 - [i13]Xin Liu, Weijia Zhang, Min-Ling Zhang:
Attention Is Not What You Need: Revisiting Multi-Instance Learning for Whole Slide Image Classification. CoRR abs/2408.09449 (2024) - [i12]Wei Tang, Weijia Zhang, Min-Ling Zhang:
Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning. CoRR abs/2408.14369 (2024) - [i11]Debo Cheng, Jiuyong Li, Lin Liu, Ziqi Xu, Weijia Zhang, Jixue Liu, Thuc Duy Le:
Disentangled Representation Learning for Causal Inference with Instruments. CoRR abs/2412.04641 (2024) - 2023
- [c6]Wei Tang, Weijia Zhang, Min-Ling Zhang:
Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning. NeurIPS 2023 - [i10]Zhaofei Wang, Weijia Zhang, Min-Ling Zhang:
Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection. CoRR abs/2303.14999 (2023) - [i9]Hanwen Deng, Weijia Zhang, Min-Ling Zhang:
Rethinking the Value of Labels for Instance-Dependent Label Noise Learning. CoRR abs/2305.06247 (2023) - [i8]Wei Tang, Weijia Zhang, Min-Ling Zhang:
Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning. CoRR abs/2305.16912 (2023) - [i7]Weijia Zhang, Chun Kai Ling, Xuanhui Zhang:
Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees. CoRR abs/2312.15566 (2023) - 2022
- [j8]Weijia Zhang, Jiuyong Li, Lin Liu:
A Unified Survey of Treatment Effect Heterogeneity Modelling and Uplift Modelling. ACM Comput. Surv. 54(8): 162:1-162:36 (2022) - [j7]Xuanhui Zhang, Weijia Zhang, Yuxiang (Chris) Zhao, Qinghua Zhu:
Imbalanced volunteer engagement in cultural heritage crowdsourcing: a task-related exploration based on causal inference. Inf. Process. Manag. 59(5): 103027 (2022) - [j6]Shujun Yang, Yu Zhang, Yuheng Jia, Weijia Zhang:
Local Low-Rank Approximation With Superpixel-Guided Locality Preserving Graph for Hyperspectral Image Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15: 7741-7754 (2022) - [c5]Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang:
Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization. NeurIPS 2022 - [i6]Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang:
Towards Learning Causal Representations from Multi-Instance Bags. CoRR abs/2202.12570 (2022) - [i5]Wei Tang, Weijia Zhang, Min-Ling Zhang:
Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision. CoRR abs/2212.08997 (2022) - 2021
- [j5]Jiuyong Li, Weijia Zhang, Lin Liu, Kui Yu, Thuc Duy Le, Jixue Liu:
A general framework for causal classification. Int. J. Data Sci. Anal. 11(2): 127-139 (2021) - [c4]Weijia Zhang, Lin Liu, Jiuyong Li:
Treatment Effect Estimation with Disentangled Latent Factors. AAAI 2021: 10923-10930 - [c3]Weijia Zhang:
Non-I.I.D. Multi-Instance Learning for Predicting Instance and Bag Labels with Variational Auto-Encoder. IJCAI 2021: 3377-3383 - 2020
- [j4]Mattia Tomasoni, Sergio Gómez, Jake Crawford, Weijia Zhang, Sarvenaz Choobdar, Daniel Marbach, Sven Bergmann:
MONET: a toolbox integrating top-performing methods for network modularization. Bioinform. 36(12): 3920-3921 (2020) - [c2]Weijia Zhang, Lin Liu, Jiuyong Li:
Robust Multi-Instance Learning with Stable Instances. ECAI 2020: 1682-1689 - [i4]Weijia Zhang, Lin Liu, Jiuyong Li:
Treatment effect estimation with disentangled latent factors. CoRR abs/2001.10652 (2020) - [i3]Jiuyong Li, Weijia Zhang, Lin Liu, Kui Yu, Thuc Duy Le, Jixue Liu:
A general framework for causal classification. CoRR abs/2003.11940 (2020) - [i2]Weijia Zhang, Jiuyong Li, Lin Liu:
A unified survey on treatment effect heterogeneity modeling and uplift modeling. CoRR abs/2007.12769 (2020)
2010 – 2019
- 2019
- [i1]Weijia Zhang, Jiuyong Li, Lin Liu:
Distributionally Robust Multi-instance Learning with Stable Instances. CoRR abs/1902.05066 (2019) - 2018
- [j3]Weijia Zhang, Thuc Duy Le, Lin Liu, Jiuyong Li:
Estimating heterogeneous treatment effect by balancing heterogeneity and fitness. BMC Bioinform. 19-S(19): 61-72 (2018) - [j2]Taosheng Xu, Ning Su, Lin Liu, Junpeng Zhang, Hongqiang Wang, Weijia Zhang, Jie Gui, Kui Yu, Jiuyong Li, Thuc Duy Le:
miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase. BMC Bioinform. 19-S(19): 179-188 (2018) - 2017
- [j1]Weijia Zhang, Thuc Duy Le, Lin Liu, Zhi-Hua Zhou, Jiuyong Li:
Mining heterogeneous causal effects for personalized cancer treatment. Bioinform. 33(15): 2372-2378 (2017) - 2014
- [c1]Weijia Zhang, Zhi-Hua Zhou:
Multi-Instance Learning with Distribution Change. AAAI 2014: 2184-2190
Coauthor Index
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