Search Results for author: Rui Xu

Found 37 papers, 9 papers with code

LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection

no code implementations3 Aug 2022 Rui Xu, Yong Luo, Bo Du, Kaiming Kuang, Jiancheng Yang

Convolutional neural networks (CNNs) have been demonstrated to be highly effective in the field of pulmonary nodule detection.

Computed Tomography (CT)

FedRel: An Adaptive Federated Relevance Framework for Spatial Temporal Graph Learning

no code implementations7 Jun 2022 Tiehua Zhang, Yuze Liu, Zhishu Shen, Rui Xu, Xin Chen, Xiaowei Huang, Xi Zheng

Spatial-temporal data contains rich information and has been widely studied in recent years due to the rapid development of relevant applications in many fields.

Federated Learning Graph Learning

Neighbors Are Not Strangers: Improving Non-Autoregressive Translation under Low-Frequency Lexical Constraints

1 code implementation NAACL 2022 Chun Zeng, Jiangjie Chen, Tianyi Zhuang, Rui Xu, Hao Yang, Ying Qin, Shimin Tao, Yanghua Xiao

To this end, we propose a plug-in algorithm for this line of work, i. e., Aligned Constrained Training (ACT), which alleviates this problem by familiarizing the model with the source-side context of the constraints.

Translation

E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning

no code implementations Findings (ACL) 2022 Jiangjie Chen, Rui Xu, Ziquan Fu, Wei Shi, Zhongqiao Li, Xinbo Zhang, Changzhi Sun, Lei LI, Yanghua Xiao, Hao Zhou

Holding the belief that models capable of reasoning should be right for the right reasons, we propose a first-of-its-kind Explainable Knowledge-intensive Analogical Reasoning benchmark (E-KAR).

Explanation Generation Question Answering

Domain Disentangled Generative Adversarial Network for Zero-Shot Sketch-Based 3D Shape Retrieval

no code implementations24 Feb 2022 Rui Xu, Zongyan Han, Le Hui, Jianjun Qian, Jin Xie

Then, we develop a generative adversarial network that combines the domain-specific features of the seen categories with the aligned domain-invariant features to synthesize samples, where the synthesized samples of the unseen categories are generated by using the corresponding word embeddings.

3D Shape Retrieval Word Embeddings

SSDL: Self-Supervised Dictionary Learning

no code implementations3 Dec 2021 Shuai Shao, Lei Xing, Wei Yu, Rui Xu, Yanjiang Wang, BaoDi Liu

Inspired by the concept of self-supervised learning (e. g., setting the pretext task to generate a universal model for the downstream task), we propose a Self-Supervised Dictionary Learning (SSDL) framework to address this challenge.

Dictionary Learning Human Activity Recognition +1

MDFM: Multi-Decision Fusing Model for Few-Shot Learning

no code implementations1 Dec 2021 Shuai Shao, Lei Xing, Rui Xu, Weifeng Liu, Yan-Jiang Wang, Bao-Di Liu

Inspired by this assumption, we propose a novel method Multi-Decision Fusing Model (MDFM), which comprehensively considers the decisions based on multiple FEMs to enhance the efficacy and robustness of the model.

Few-Shot Learning

Uncertainty quantification and inverse modeling for subsurface flow in 3D heterogeneous formations using a theory-guided convolutional encoder-decoder network

no code implementations14 Nov 2021 Rui Xu, Dongxiao Zhang, Nanzhe Wang

The surrogate models are used to conduct uncertainty quantification considering a stochastic permeability field, as well as to infer unknown permeability information based on limited well production data and observation data of formation properties.

The Nuts and Bolts of Adopting Transformer in GANs

no code implementations25 Oct 2021 Rui Xu, Xiangyu Xu, Kai Chen, Bolei Zhou, Chen Change Loy

Transformer becomes prevalent in computer vision, especially for high-level vision tasks.

Image Generation

Learning Symmetric Locomotion using Cumulative Fatigue for Reinforcement Learning

no code implementations29 Sep 2021 Rui Xu, Noshaba Cheema, Erik Herrmann, Perttu Hämäläinen, Philipp Slusallek

One explanation for this is that present RL models do not estimate biomechanical effort; instead, they minimize instantaneous squared joint actuation torques as a proxy for the actual subjective cost of actions.

reinforcement-learning

Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolution

no code implementations CVPR 2021 Baoli Sun, Xinchen Ye, Baopu Li, Haojie Li, Zhihui Wang, Rui Xu

First, we design a cross-task distillation scheme that encourages DSR and DE networks to learn from each other in a teacher-student role-exchanging fashion.

Depth Estimation Super-Resolution +1

BaPipe: Exploration of Balanced Pipeline Parallelism for DNN Training

no code implementations23 Dec 2020 Letian Zhao, Rui Xu, Tianqi Wang, Teng Tian, Xiaotian Wang, Wei Wu, Chio-in Ieong, Xi Jin

The size of deep neural networks (DNNs) grows rapidly as the complexity of the machine learning algorithm increases.

Positional Encoding as Spatial Inductive Bias in GANs

no code implementations CVPR 2021 Rui Xu, Xintao Wang, Kai Chen, Bolei Zhou, Chen Change Loy

In this work, taking SinGAN and StyleGAN2 as examples, we show that such capability, to a large extent, is brought by the implicit positional encoding when using zero padding in the generators.

Image Manipulation Inductive Bias +1

CARAFE++: Unified Content-Aware ReAssembly of FEatures

no code implementations7 Dec 2020 Jiaqi Wang, Kai Chen, Rui Xu, Ziwei Liu, Chen Change Loy, Dahua Lin

Feature reassembly, i. e. feature downsampling and upsampling, is a key operation in a number of modern convolutional network architectures, e. g., residual networks and feature pyramids.

Image Inpainting Instance Segmentation +3

Precessions of Spheroidal Stars under Lorentz Violation and Observational Consequences

no code implementations2 Dec 2020 Rui Xu, Yong Gao, Lijing Shao

The Standard-Model Extension (SME) is an effective-field-theoretic framework that catalogs all Lorentz-violating field operators.

General Relativity and Quantum Cosmology High Energy Astrophysical Phenomena High Energy Physics - Phenomenology

DLDL: Dynamic Label Dictionary Learning via Hypergraph Regularization

no code implementations23 Oct 2020 Shuai Shao, Mengke Wang, Rui Xu, Yan-Jiang Wang, Bao-Di Liu

To tackle this issue, we propose a Dynamic Label Dictionary Learning (DLDL) algorithm to generate the soft label matrix for unlabeled data.

Dictionary Learning

SAHDL: Sparse Attention Hypergraph Regularized Dictionary Learning

no code implementations23 Oct 2020 Shuai Shao, Rui Xu, Yan-Jiang Wang, Weifeng Liu, Bao-Di Liu

In this paper, we propose a hypergraph based sparse attention mechanism to tackle this issue and embed it into dictionary learning.

Dictionary Learning

VolumeNet: A Lightweight Parallel Network for Super-Resolution of Medical Volumetric Data

no code implementations16 Oct 2020 Yinhao Li, Yutaro Iwamoto, Lanfen Lin, Rui Xu, Yen-Wei Chen

We construct a parallel connection structure based on the group convolution and feature aggregation to build a 3D CNN that is as wide as possible with few parameters.

Super-Resolution

Texture Memory-Augmented Deep Patch-Based Image Inpainting

1 code implementation28 Sep 2020 Rui Xu, Minghao Guo, Jiaqi Wang, Xiaoxiao Li, Bolei Zhou, Chen Change Loy

By bringing together the best of both paradigms, we propose a new deep inpainting framework where texture generation is guided by a texture memory of patch samples extracted from unmasked regions.

Image Inpainting Texture Synthesis

Weak Form Theory-guided Neural Network (TgNN-wf) for Deep Learning of Subsurface Single and Two-phase Flow

no code implementations8 Sep 2020 Rui Xu, Dongxiao Zhang, Miao Rong, Nanzhe Wang

In the weak form, high order derivatives in the PDE can be transferred to the test functions by performing integration-by-parts, which reduces computational error.

Progressive Point Cloud Deconvolution Generation Network

1 code implementation ECCV 2020 Le Hui, Rui Xu, Jin Xie, Jianjun Qian, Jian Yang

Starting from the low-resolution point clouds, with the bilateral interpolation and max-pooling operations, the deconvolution network can progressively output high-resolution local and global feature maps.

Point Cloud Generation

Discovering Symbolic Models from Deep Learning with Inductive Biases

3 code implementations NeurIPS 2020 Miles Cranmer, Alvaro Sanchez-Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer, David Spergel, Shirley Ho

The technique works as follows: we first encourage sparse latent representations when we train a GNN in a supervised setting, then we apply symbolic regression to components of the learned model to extract explicit physical relations.

Symbolic Regression

Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network

no code implementations24 Apr 2020 Rui Xu, Tiantian Liu, Xinchen Ye, Yen-Wei Chen

Many deep learning based methods have been proposed for retinal vessel segmentation, however few of them focus on the connectivity of segmented vessels, which is quite important for a practical computer-aided diagnosis system on retinal images.

Retinal Vessel Segmentation

Implications of the virus-encoded miRNA and host miRNA in the pathogenicity of SARS-CoV-2

no code implementations10 Apr 2020 Zhi Liu, Jianwei Wang, Yuyu Xu, Mengchen Guo, Kai Mi, Rui Xu, Yang Pei, Qiangkun Zhang, Xiaoting Luan, Zhibin Hu, Xingyin Liu#

The outbreak of COVID-19 caused by SARS-CoV-2 has rapidly spread worldwide and has caused over 1, 400, 000 infections and 80, 000 deaths.

Genomics Biomolecules

Hearing Lips: Improving Lip Reading by Distilling Speech Recognizers

no code implementations26 Nov 2019 Ya Zhao, Rui Xu, Xinchao Wang, Peng Hou, Haihong Tang, Mingli Song

In this paper, we propose a new method, termed as Lip by Speech (LIBS), of which the goal is to strengthen lip reading by learning from speech recognizers.

 Ranked #1 on Lipreading on CMLR

Knowledge Distillation Lipreading +3

Learning Symbolic Physics with Graph Networks

no code implementations12 Sep 2019 Miles D. Cranmer, Rui Xu, Peter Battaglia, Shirley Ho

We introduce an approach for imposing physically motivated inductive biases on graph networks to learn interpretable representations and improved zero-shot generalization.

Inductive Bias Symbolic Regression

A Cascade Sequence-to-Sequence Model for Chinese Mandarin Lip Reading

no code implementations14 Aug 2019 Ya Zhao, Rui Xu, Mingli Song

When trained on CMLR dataset, the proposed CSSMCM surpasses the performance of state-of-the-art lip reading frameworks, which confirms the effectiveness of explicit modeling of tones for Chinese Mandarin lip reading.

Lipreading Lip Reading

Deep Flow-Guided Video Inpainting

2 code implementations CVPR 2019 Rui Xu, Xiaoxiao Li, Bolei Zhou, Chen Change Loy

Then the synthesized flow field is used to guide the propagation of pixels to fill up the missing regions in the video.

One-shot visual object segmentation Optical Flow Estimation +2

CARAFE: Content-Aware ReAssembly of FEatures

2 code implementations ICCV 2019 Jiaqi Wang, Kai Chen, Rui Xu, Ziwei Liu, Chen Change Loy, Dahua Lin

CARAFE introduces little computational overhead and can be readily integrated into modern network architectures.

Instance Segmentation object-detection +2

Label Embedded Dictionary Learning for Image Classification

1 code implementation7 Mar 2019 Shuai Shao, Yan-Jiang Wang, Bao-Di Liu, Weifeng Liu, Rui Xu

Recently, label consistent k-svd (LC-KSVD) algorithm has been successfully applied in image classification.

Classification Dictionary Learning +2

Power Plant Performance Modeling with Concept Drift

no code implementations19 Oct 2017 Rui Xu, Yunwen Xu, Weizhong Yan

Power plant is a complex and nonstationary system for which the traditional machine learning modeling approaches fall short of expectations.

Machine Learning online learning

Concept Drift Learning with Alternating Learners

no code implementations18 Oct 2017 Yunwen Xu, Rui Xu, Weizhong Yan, Paul Ardis

Data-driven predictive analytics are in use today across a number of industrial applications, but further integration is hindered by the requirement of similarity among model training and test data distributions.

Linear Vlasov theory of a magnetised, thermally stratified atmosphere

1 code implementation18 Aug 2016 Rui Xu, Matthew W. Kunz

At sub-ion-Larmor scales, we discover an overstability driven by the electron temperature gradient of kinetic-Alfv\'en drift waves -- the electron MTI (eMTI) -- whose growth rate is even larger than the standard MTI.

High Energy Astrophysical Phenomena Plasma Physics

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