Weijia Zhang

Orcid: 0000-0001-8103-5325

Affiliations:
  • University of Newcastle, School of Information and Physical Sciences, NSW, Australia
  • Southeast University, Nanjing, China (2021 - 2023)
  • University of South Australia, Australia (PhD 2018)
  • Nanjing University, China (former)


According to our database1, Weijia Zhang authored at least 24 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2024
Attention Is Not What You Need: Revisiting Multi-Instance Learning for Whole Slide Image Classification.
CoRR, 2024

Multi-instance partial-label learning: towards exploiting dual inexact supervision.
Sci. China Inf. Sci., 2024

Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Proposal Feature Learning Using Proposal Relations for Weakly Supervised Object Detection.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Rethinking the Value of Labels for Instance-Dependent Label Noise Learning.
CoRR, 2023

Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection.
CoRR, 2023

Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning.
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.
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.
Inf. Process. Manag., 2022

A Unified Survey of Treatment Effect Heterogeneity Modelling and Uplift Modelling.
ACM Comput. Surv., 2022

Towards Learning Causal Representations from Multi-Instance Bags.
CoRR, 2022

Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization.
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.
Int. J. Data Sci. Anal., 2021

Non-I.I.D. Multi-Instance Learning for Predicting Instance and Bag Labels with Variational Auto-Encoder.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Treatment Effect Estimation with Disentangled Latent Factors.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
A unified survey on treatment effect heterogeneity modeling and uplift modeling.
CoRR, 2020

MONET: a toolbox integrating top-performing methods for network modularization.
Bioinform., 2020

Robust Multi-Instance Learning with Stable Instances.
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.
CoRR, 2019

2018
Estimating heterogeneous treatment effect by balancing heterogeneity and fitness.
BMC Bioinform., 2018

miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase.
BMC Bioinform., 2018

2017
Mining heterogeneous causal effects for personalized cancer treatment.
Bioinform., 2017

2014
Multi-Instance Learning with Distribution Change.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014


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