Search Results for author: Yuhao Wang

Found 25 papers, 13 papers with code

Generative Modeling in Structural-Hankel Domain for Color Image Inpainting

no code implementations25 Nov 2022 Zihao Li, CHUNHUA WU, Shenglin Wu, Wenbo Wan, Yuhao Wang, Qiegen Liu

To better apply the score-based generative model to learn the internal statistical distribution within patches, the large-scale Hankel matrices are finally folded into the higher dimensional tensors for prior learning.

Image Inpainting

Generative Modeling in Sinogram Domain for Sparse-view CT Reconstruction

no code implementations25 Nov 2022 Bing Guan, Cailian Yang, Liu Zhang, Shanzhou Niu, Minghui Zhang, Yuhao Wang, Weiwen Wu, Qiegen Liu

When the number of projection view changes, the DL network should be retrained with updated sparse-view/full-view CT image pairs.

Computed Tomography (CT) Image Reconstruction

Self adaptive global-local feature enhancement for radiology report generation

no code implementations21 Nov 2022 Yuhao Wang, Kai Wang, Xiaohong Liu, Tianrun Gao, Jingyue Zhang, Guangyu Wang

Automated radiology report generation aims at automatically generating a detailed description of medical images, which can greatly alleviate the workload of radiologists and provide better medical services to remote areas.

Anatomy

Factorized Blank Thresholding for Improved Runtime Efficiency of Neural Transducers

no code implementations2 Nov 2022 Duc Le, Frank Seide, Yuhao Wang, Yang Li, Kjell Schubert, Ozlem Kalinli, Michael L. Seltzer

Since the blank probability can be computed very efficiently and the RNN-T output is dominated by blanks, our proposed method leads to a 26-30% decoding speed-up and 43-53% reduction in on-device power consumption, all the while incurring no accuracy degradation and being relatively simple to implement.

Risk-averse Contextual Multi-armed Bandit Problem with Linear Payoffs

no code implementations24 Jun 2022 Yifan Lin, Yuhao Wang, Enlu Zhou

In particular, we consider mean-variance as the risk criterion, and the best arm is the one with the largest mean-variance reward.

Thompson Sampling

Long-term Causal Inference Under Persistent Confounding via Data Combination

no code implementations15 Feb 2022 Guido Imbens, Nathan Kallus, Xiaojie Mao, Yuhao Wang

In this paper, we uniquely tackle the challenge of persistent unmeasured confounders, i. e., some unmeasured confounders that can simultaneously affect the treatment, short-term outcomes and the long-term outcome, noting that they invalidate identification strategies in previous literature.

Causal Inference

Variable Augmented Network for Invertible MR Coil Compression

1 code implementation19 Jan 2022 Xianghao Liao, Shanshan Wang, Lanlan Tu, Yuhao Wang, Dong Liang, Qiegen Liu

Additionally, its performance is not susceptible to different number of virtual coils.

Virtual Coil Augmentation Technology for MR Coil Extrapolation via Deep Learning

no code implementations19 Jan 2022 Cailian Yang, Xianghao Liao, Yuhao Wang, Minghui Zhang, Qiegen Liu

Two main components are incorporated into the network design, namely variable augmentation technology and sum of squares (SOS) objective function.

Image Reconstruction Super-Resolution

MRI Reconstruction Using Deep Energy-Based Model

1 code implementation7 Sep 2021 Yu Guan, Zongjiang Tu, Shanshan Wang, Qiegen Liu, Yuhao Wang, Dong Liang

In contrast to other generative models for reconstruction, the proposed method utilizes deep energy-based information as the image prior in reconstruction to improve the quality of image.

Image Generation MRI Reconstruction

Variable Augmented Network for Invertible Modality Synthesis-Fusion

1 code implementation2 Sep 2021 Yuhao Wang, Ruirui Liu, Zihao Li, Cailian Yang, Qiegen Liu

As an effective way to integrate the information contained in multiple medical images under different modalities, medical image synthesis and fusion have emerged in various clinical applications such as disease diagnosis and treatment planning.

Image Generation

High-dimensional Assisted Generative Model for Color Image Restoration

1 code implementation14 Aug 2021 Kai Hong, CHUNHUA WU, Cailian Yang, Minghui Zhang, Yancheng Lu, Yuhao Wang, Qiegen Liu

This work presents an unsupervised deep learning scheme that exploiting high-dimensional assisted score-based generative model for color image restoration tasks.

Demosaicking Denoising

Learning Sparse Fixed-Structure Gaussian Bayesian Networks

1 code implementation22 Jul 2021 Arnab Bhattacharyya, Davin Choo, Rishikesh Gajjala, Sutanu Gayen, Yuhao Wang

We also study a couple of new algorithms for the problem: - BatchAvgLeastSquares takes the average of several batches of least squares solutions at each node, so that one can interpolate between the batch size and the number of batches.

Wavelet Transform-assisted Adaptive Generative Modeling for Colorization

4 code implementations9 Jul 2021 Jin Li, Wanyun Li, Zichen Xu, Yuhao Wang, Qiegen Liu

Unsupervised deep learning has recently demonstrated the promise of producing high-quality samples.

Colorization Denoising +1

Identifiability of AMP chain graph models

1 code implementation17 Jun 2021 Yuhao Wang, Arnab Bhattacharyya

AMP models are described by DAGs on chain components which themselves are undirected graphs.

Direction-Aggregated Attack for Transferable Adversarial Examples

1 code implementation19 Apr 2021 Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy

Deep neural networks are vulnerable to adversarial examples that are crafted by imposing imperceptible changes to the inputs.

Sparse Code Multiple Access for 6G Wireless Communication Networks: Recent Advances and Future Directions

no code implementations3 Apr 2021 Lisu Yu, Zilong Liu, Miaowen Wen, Donghong Cai, Shuping Dang, Yuhao Wang, Pei Xiao

As 5G networks rolling out in many different countries nowadays, the time has come to investigate how to upgrade and expand them towards 6G, where the latter is expected to realize the interconnection of everything as well as the development of a ubiquitous intelligent mobile world for intelligent life.

Joint Intensity-Gradient Guided Generative Modeling for Colorization

6 code implementations28 Dec 2020 Kai Hong, Jin Li, Wanyun Li, Cailian Yang, Minghui Zhang, Yuhao Wang, Qiegen Liu

Furthermore, the joint intensity-gradient constraint in data-fidelity term is proposed to limit the degree of freedom within generative model at the iterative colorization stage, and it is conducive to edge-preserving.

Colorization

Amortized Variational Deep Q Network

1 code implementation3 Nov 2020 Haotian Zhang, Yuhao Wang, Jianyong Sun, Zongben Xu

Efficient exploration is one of the most important issues in deep reinforcement learning.

Efficient Exploration OpenAI Gym +1

Joint Inference of Multiple Graphs from Matrix Polynomials

no code implementations16 Oct 2020 Madeline Navarro, Yuhao Wang, Antonio G. Marques, Caroline Uhler, Santiago Segarra

Inferring graph structure from observations on the nodes is an important and popular network science task.

Learning in the Frequency Domain

4 code implementations CVPR 2020 Kai Xu, Minghai Qin, Fei Sun, Yuhao Wang, Yen-Kuang Chen, Fengbo Ren

Experiment results show that learning in the frequency domain with static channel selection can achieve higher accuracy than the conventional spatial downsampling approach and meanwhile further reduce the input data size.

Instance Segmentation Semantic Segmentation

Causal Discovery from Incomplete Data: A Deep Learning Approach

no code implementations15 Jan 2020 Yuhao Wang, Vlado Menkovski, Hao Wang, Xin Du, Mykola Pechenizkiy

As systems are getting more autonomous with the development of artificial intelligence, it is important to discover the causal knowledge from observational sensory inputs.

Causal Discovery Imputation

DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks

no code implementations19 Nov 2019 Ao Ren, Tao Zhang, Yuhao Wang, Sheng Lin, Peiyan Dong, Yen-Kuang Chen, Yuan Xie, Yanzhi Wang

As a further optimization, we propose a density-adaptive regular-block (DARB) pruning that outperforms prior structured pruning work with high pruning ratio and decoding efficiency.

Model Compression Network Pruning

Learning Priors in High-frequency Domain for Inverse Imaging Reconstruction

1 code implementation23 Oct 2019 Zhuonan He, Jinjie Zhou, Dong Liang, Yuhao Wang, Qiegen Liu

Ill-posed inverse problems in imaging remain an active research topic in several decades, with new approaches constantly emerging.

Denoising Dictionary Learning

Direct Estimation of Differences in Causal Graphs

1 code implementation NeurIPS 2018 Yuhao Wang, Chandler Squires, Anastasiya Belyaeva, Caroline Uhler

We consider the problem of estimating the differences between two causal directed acyclic graph (DAG) models given i. i. d.~samples from each model.

Methodology

Permutation-based Causal Inference Algorithms with Interventions

no code implementations NeurIPS 2017 Yuhao Wang, Liam Solus, Karren Yang, Caroline Uhler

Learning directed acyclic graphs using both observational and interventional data is now a fundamentally important problem due to recent technological developments in genomics that generate such single-cell gene expression data at a very large scale.

Causal Inference

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