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Shuai Jiang

7 accepted papers

2026

Interpretability and Generalization Bounds for Learning Spatial Physics

ICML 2026poster

While there are many applications of machine learning (ML) to scientific problems that \emph{look} promising, the eye test can be misleading compared to the quantitative values. Using numerical analysis techniques, we rigorously quantify the accuracy, convergence rates, and generalization bounds of …

Cited by 0SourceScholar
2026

On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime

ICLR 2026poster

Spectral bias, the tendency of neural networks to learn low frequencies first, can be both a blessing and a curse. While it enhances the generalization capabilities by suppressing high-frequency noise, it can be a limitation in scientific tasks that require capturing fine-scale structures. The delay…

Cited by 0SourceScholar
2026

Structured Multi-modal Graph Disentanglement for Psychiatric Diagnosis

ICML 2026poster

Multi-modal neuroimaging diagnosis must integrate cross-modal agreement with modality-specific complementarity, yet in real multi-site cohorts these signals are frequently entangled with site- and cohort-dependent correlations, yielding shortcut-driven predictions, fragile transfer, and limited inte…

Cited by 0SourceScholar
2025

Prompt-driven Transferable Adversarial Attack on Person Re-Identification with Attribute-aware Textual Inversion

ICCV 2025poster

Person re-identification (re-id) models are vital in security surveillance systems, requiring transferable adversarial attacks to explore the vulnerabilities of them. Recently, vision-language models (VLM) based attacks have shown superior transferability by attacking generalized image and textual f…

2025

Searching Efficient Semantic Segmentation Architectures via Dynamic Path Selection

NeurIPS 2025poster

Existing NAS methods for semantic segmentation typically apply uniform optimization to all candidate networks (paths) within a one-shot supernet. However, the concurrent existence of both promising and suboptimal paths often results in inefficient weight updates and gradient conflicts. This issue is…

Cited by 0SourceScholar
2023

Mutually Guided Few-Shot Learning For Relational Triple Extraction

ICASSP 2023accepted

Knowledge graphs (KGs), containing many entity-relation-entity triples, provide rich information for downstream applications. Although extracting triples from unstructured texts has been widely explored, most of them require a large number of labeled instances. The performance will drop dramatically…

Cited by 0SourceScholar
2020

End-to-end Dynamic Matching Network for Multi-view Multi-person 3d Pose Estimation

ECCV 2020poster

As an important computer vision task, 3d human pose estimation in a multi-camera, multi-person setting has received widespread attention and many interesting applications have been derived from it. Traditional approaches use a 3d pictorial structure model to handle this task. However, these models s…

Cited by 50SourcePDFScholar