Search Results for author: Yingjie Liu

Found 7 papers, 0 papers with code

Neural Network with Local Converging Input (NNLCI) for Supersonic Flow Problems with Unstructured Grids

no code implementations23 Oct 2023 Weiming Ding, Haoxiang Huang, Tzu Jung Lee, Yingjie Liu, Vigor Yang

In the present study, we develop a neural network with local converging input (NNLCI) for high-fidelity prediction using unstructured data.

A Survey of Geometric Optimization for Deep Learning: From Euclidean Space to Riemannian Manifold

no code implementations16 Feb 2023 Yanhong Fei, Xian Wei, Yingjie Liu, Zhengyu Li, Mingsong Chen

Although Deep Learning (DL) has achieved success in complex Artificial Intelligence (AI) tasks, it suffers from various notorious problems (e. g., feature redundancy, and vanishing or exploding gradients), since updating parameters in Euclidean space cannot fully exploit the geometric structure of the solution space.

Transfer Learning

Solving Maxwell's Equation in 2D with Neural Networks with Local Converging Inputs

no code implementations6 Feb 2023 Harris Cobb, Hwi Lee, Yingjie Liu

In contrast with existing research work on applying neural networks to directly solve PDEs, our method takes advantage of the local domain of dependence of the Maxwell's equation in the input solution patches, and is therefore simpler, yet still robust.

O-ViT: Orthogonal Vision Transformer

no code implementations28 Jan 2022 Yanhong Fei, Yingjie Liu, Xian Wei, Mingsong Chen

Inspired by the tremendous success of the self-attention mechanism in natural language processing, the Vision Transformer (ViT) creatively applies it to image patch sequences and achieves incredible performance.

Dense Multiscale Feature Fusion Pyramid Networks for Object Detection in UAV-Captured Images

no code implementations19 Dec 2020 Yingjie Liu

Although much significant progress has been made in the research field of object detection with deep learning, there still exists a challenging task for the objects with small size, which is notably pronounced in UAV-captured images.

object-detection Object Detection

IDENT: Identifying Differential Equations with Numerical Time evolution

no code implementations6 Apr 2019 Sung Ha Kang, Wenjing Liao, Yingjie Liu

The new algorithm, called Identifying Differential Equations with Numerical Time evolution (IDENT), is explored for data with non-periodic boundary conditions, noisy data and PDEs with varying coefficients.

Numerical Analysis

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