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Runzhao Yang

7 accepted papers

2025

A Compact Implicit Neural Representation for Efficient Storage of Massive 4D Functional Magnetic Resonance Imaging

AAAI 2025technical

Functional Magnetic Resonance Imaging (fMRI) data is a widely used kind of four-dimensional biomedical data, which requires effective compression. However, fMRI compressing poses unique challenges due to its intricate temporal dynamics, low signal-to-noise ratio, and complicated underlying redundanc…

Cited by 0SourcePDFScholar
2025

DVI:A Derivative-based Vision Network for INR

ICML 2025poster

Recent advancements in computer vision have seen Implicit Neural Representations (INR) becoming a dominant representation form for data due to their compactness and expressive power. To solve various vision tasks with INR data, vision networks can either be purely INR-based, but are thereby limited…

Cited by 0SourcePDFScholar
2024

A Physics-informed Low-rank Deep Neural Network for Blind and Universal Lens Aberration Correction

CVPR 2024poster

High-end lenses although offering high-quality images suffer from both insufficient affordability and bulky design which hamper their applications in low-budget scenarios or on low-payload platforms. A flexible scheme is to tackle the optical aberration of low-end lenses computationally. However it…

Cited by 8SourcePDFScholar
2024

SHoP: A Deep Learning Framework for Solving High-Order Partial Differential Equations

AAAI 2024technical

Solving partial differential equations (PDEs) has been a fundamental problem in computational science and of wide applications for both scientific and engineering research. Due to its universal approximation property, neural network is widely used to approximate the solutions of PDEs. However, exist…

2023

CUTS: Neural Causal Discovery from Irregular Time-Series Data

ICLR 2023poster

Causal discovery from time-series data has been a central task in machine learning. Recently, Granger causality inference is gaining momentum due to its good explainability and high compatibility with emerging deep neural networks. However, most existing methods assume structured input data and dege…

2023

SCI: A Spectrum Concentrated Implicit Neural Compression for Biomedical Data

AAAI 2023technical

Massive collection and explosive growth of biomedical data, demands effective compression for efficient storage, transmission and sharing. Readily available visual data compression techniques have been studied extensively but tailored for natural images/videos, and thus show limited performance on b…