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Badong Chen

As seen in: Nature, arXiv, Frontiers
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Articles by Badong Chen

Brain contrastive modeling reveals depression subtypes with distinct treatment response and progression

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By Kaizhong Zheng, Xinhu Zheng, Hongyu Shi, Liangjun Chen, Lingjiang Li, Dewen Hu, Karl Friston, Huaning Wang, Baojuan Li, Badong Chen
| Nature Verified
Abstract Major Depressive Disorder (MDD) is highly heterogeneous, limiting treatment efficacy. Despite efforts to delineate patient heterogeneity through subtyping, current approaches remain limited by noise, lack of clinical applicability, and insufficient external validation. Crucially, they focus on subtyping while neglecting staging information (e.g., illness duration). We developed BrainCVAE, a contrastive variational autoencoder, to disentangle MDD-specific neural features.
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Efficient training of neuromorphic electronics

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By Shuangming Yang, Jianshi Tang, Tianhang Zhou, Bernabe Linares-Barranco, Giacomo Indiveri, Xinhu Zheng, Mostafa Rahimi Azghadi, Badong Chen
| Nature Verified
Abstract Neuromorphic electronics can provide in-memory computing systems with low power consumption by emulating key principles of the brain. However, their practical capabilities are limited by a number of challenges, including device non-ideality, limited training accuracy and insufficient adaptability. Here we explore the development of training approaches for neuromorphic electronics, including digital, mixed-signal and emerging neuromorphic electronics.
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Relation DETR: Exploring Explicit Position Relation Prior for Object Detection

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By Meiqin Liu, Senlin Zhang, Ping Wei, Badong Chen
| arXiv
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[2405.08779] Jacobian Regularizer-based Neural Granger Causality

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By Shuanghao Bai, Shujian Yu, Qibin Zhao, Badong Chen
| arXiv
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Revisiting the Adversarial Robustness of Vision Language Models: a Multimodal Perspective

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By Shuanghao Bai, Qibin Zhao, Badong Chen
| arXiv
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[2403.18393] Tensor-based Graph Learning with Consistency and Specificity for Multi-view Clustering

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By Lei Cao, Yu Zhao, Badong Chen, Yunshan Ye
| arXiv
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Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement

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By Meiqin Liu, Senlin Zhang, Ping Wei, Badong Chen
| arXiv
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CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis

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By Shujian Yu, Badong Chen
| arXiv
[Submitted on 4 Jan 2023 ( v1 ), last revised 28 Jan 2024 (this version, v3)] Title:CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis Download a PDF of the paper titled CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis, by Kaizhong Zheng and 2 other authors Download PDF HTML (experimental) Abstract:There is a recent trend to leverage the power of graph neural...
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