Mingxuan Liu | DeepAI

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Featured Co-authors

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Zhun Zhong
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Haoxiang Li
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∙ 09/05/2023

SAM-Deblur: Let Segment Anything Boost Image Deblurring

Image deblurring is a critical task in the field of image restoration, a...

0 Siwei Li, et al. ∙

∙ 08/20/2023

Spiking-Diffusion: Vector Quantized Discrete Diffusion Model with Spiking Neural Networks

Spiking neural networks (SNNs) have tremendous potential for energy-effi...

0 Mingxuan Liu, et al. ∙

∙ 04/26/2023

Towards clinical AI fairness: A translational perspective

Artificial intelligence (AI) has demonstrated the ability to extract ins...

0 Mingxuan Liu, et al. ∙

∙ 03/28/2023

Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery

Discovering novel concepts from unlabelled data and in a continuous mann...

0 Mingxuan Liu, et al. ∙

∙ 03/01/2023

FedScore: A privacy-preserving framework for federated scoring system development

We propose FedScore, a privacy-preserving federated learning framework f...

1 Siqi Li, et al. ∙

∙ 12/16/2022

Shapley variable importance cloud for machine learning models

Current practice in interpretable machine learning often focuses on expl...

0 Yilin Ning, et al. ∙

∙ 10/15/2022

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques

Objective: The proper handling of missing values is critical to deliveri...

0 Mingxuan Liu, et al. ∙

∙ 07/18/2022

Class-incremental Novel Class Discovery

We study the new task of class-incremental Novel Class Discovery (class-...

14 Subhankar Roy, et al. ∙

∙ 06/08/2022

Balanced background and explanation data are needed in explaining deep learning models with SHAP: An empirical study on clinical decision making

Objective: Shapley additive explanations (SHAP) is a popular post-hoc te...

0 Mingxuan Liu, et al. ∙

∙ 04/24/2022

An empirical study of the effect of background data size on the stability of SHapley Additive exPlanations (SHAP) for deep learning models

Nowadays, the interpretation of why a machine learning (ML) model makes ...

0 Han Yuan, et al. ∙

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