Search Results for author: Bei Yu

Found 41 papers, 14 papers with code

Detecting Health Advice in Medical Research Literature

1 code implementation EMNLP 2021 Yingya Li, Jun Wang, Bei Yu

We also conducted a case study that applied this prediction model to retrieve specific health advice on COVID-19 treatments from LitCovid, a large COVID research literature portal, demonstrating the usefulness of retrieving health advice sentences as an advanced research literature navigation function for health researchers and the general public.


DiffPattern: Layout Pattern Generation via Discrete Diffusion

no code implementations23 Mar 2023 Zixiao Wang, Yunheng Shen, Wenqian Zhao, Yang Bai, Guojin Chen, Farzan Farnia, Bei Yu

Deep generative models dominate the existing literature in layout pattern generation.

DevelSet: Deep Neural Level Set for Instant Mask Optimization

no code implementations18 Mar 2023 Guojin Chen, Ziyang Yu, Hongduo Liu, Yuzhe ma, Bei Yu

To further enhance printability and fast iterative convergence, we propose a novel deep neural network delicately designed with level set intrinsic principles to facilitate the joint optimization of DNN and GPU accelerated level set optimizer.

AdaOPC: A Self-Adaptive Mask Optimization Framework For Real Design Patterns

no code implementations15 Mar 2023 Wenqian Zhao, Xufeng Yao, Ziyang Yu, Guojin Chen, Yuzhe ma, Bei Yu, Martin D. F. Wong

We inspect the pattern distribution on a design layer and find that different sub-regions have different pattern complexity.

Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields

no code implementations15 Mar 2023 Guojin Chen, Zehua Pei, HaoYu Yang, Yuzhe ma, Bei Yu, Martin D. F. Wong

Lithography is fundamental to integrated circuit fabrication, necessitating large computation overhead.


Generalized Parametric Contrastive Learning

2 code implementations26 Sep 2022 Jiequan Cui, Zhisheng Zhong, Zhuotao Tian, Shu Liu, Bei Yu, Jiaya Jia

Based on theoretical analysis, we observe that supervised contrastive loss tends to bias high-frequency classes and thus increases the difficulty of imbalanced learning.

Contrastive Learning Domain Generalization +3

Rethinking Graph Neural Networks for the Graph Coloring Problem

no code implementations15 Aug 2022 Wei Li, Ruxuan Li, Yuzhe ma, Siu On Chan, David Pan, Bei Yu

Graph coloring, a classical and critical NP-hard problem, is the problem of assigning connected nodes as different colors as possible.

Towards Real-World Video Denosing: A Practical Video Denosing Dataset and Network

no code implementations4 Jul 2022 Xiaogang Xu, Yitong Yu, Nianjuan Jiang, Jiangbo Lu, Bei Yu, Jiaya Jia

Moreover, we also propose a new video denoising framework, called Recurrent Video Denoising Transformer (RVDT), which can achieve SOTA performance on PVDD and other current video denoising benchmarks.

Denoising Video Denoising

DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D Detectors

1 code implementation6 Apr 2022 Yilun Chen, Shijia Huang, Shu Liu, Bei Yu, Jiaya Jia

First, to effectively lift the 2D information to stereo volume, we propose depth-wise plane sweeping (DPS) that allows denser connections and extracts depth-guided features.

3D Object Detection From Stereo Images

Eventor: An Efficient Event-Based Monocular Multi-View Stereo Accelerator on FPGA Platform

no code implementations29 Mar 2022 Mingjun Li, Jianlei Yang, Yingjie Qi, Meng Dong, Yuhao Yang, Runze Liu, Weitao Pan, Bei Yu, Weisheng Zhao

In this paper, Eventor is proposed as a fast and efficient EMVS accelerator by realizing the most critical and time-consuming stages including event back-projection and volumetric ray-counting on FPGA.


PCL: Proxy-Based Contrastive Learning for Domain Generalization

1 code implementation CVPR 2022 Xufeng Yao, Yang Bai, Xinyun Zhang, Yuechen Zhang, Qi Sun, Ran Chen, Ruiyu Li, Bei Yu

Domain generalization refers to the problem of training a model from a collection of different source domains that can directly generalize to the unseen target domains.

Contrastive Learning Domain Generalization

Conditional Temporal Variational AutoEncoder for Action Video Prediction

no code implementations12 Aug 2021 Xiaogang Xu, Yi Wang, LiWei Wang, Bei Yu, Jiaya Jia

To synthesize a realistic action sequence based on a single human image, it is crucial to model both motion patterns and diversity in the action video.

motion prediction Video Prediction

Linking Health News to Research Literature

1 code implementation14 Jul 2021 Jun Wang, Bei Yu

Accurately linking news articles to scientific research works is a critical component in a number of applications, such as measuring the social impact of a research work and detecting inaccuracies or distortions in science news.

named-entity-recognition Named Entity Recognition +1

Self Promotion in US Congressional Tweets

1 code implementation NAACL 2021 Jun Wang, Kelly Cui, Bei Yu

Prior studies have found that women self-promote less than men due to gender stereotypes.

Routing Towards Discriminative Power of Class Capsules

no code implementations7 Mar 2021 HaoYu Yang, Shuhe Li, Bei Yu

The activation of lower layer capsules affects the behavior of the following capsules via routing links that are constructed during training via certain routing algorithms.

Rethinking Graph Neural Networks for Graph Coloring

no code implementations1 Jan 2021 Wei Li, Ruxuan Li, Yuzhe ma, Siu On Chan, Bei Yu

To characterize the power of GNNs for the graph coloring problem, we first formalize the discrimination power of GNNs as the capability to assign nodes different colors.

Measuring Correlation-to-Causation Exaggeration in Press Releases

1 code implementation COLING 2020 Bei Yu, Jun Wang, Lu Guo, Yingya Li

By comparing the claims made in a press release with the corresponding claims in the original research paper, we found that 22{\%} of press releases made exaggerated causal claims from correlational findings in observational studies.

Tensor Low-Rank Reconstruction for Semantic Segmentation

no code implementations ECCV 2020 Wanli Chen, Xinge Zhu, Ruoqi Sun, Junjun He, Ruiyu Li, Xiaoyong Shen, Bei Yu

Then we use these rank-1 tensors to recover the high-rank context features through our proposed tensor reconstruction module (TRM).

Semantic Segmentation

Dive Deeper Into Box for Object Detection

no code implementations ECCV 2020 Ran Chen, Yong liu, Mengdan Zhang, Shu Liu, Bei Yu, Yu-Wing Tai

Anchor free methods have defined the new frontier in state-of-the-art object detection researches where accurate bounding box estimation is the key to the success of these methods.

object-detection Object Detection

Attacking Split Manufacturing from a Deep Learning Perspective

no code implementations8 Jul 2020 Haocheng Li, Satwik Patnaik, Abhrajit Sengupta, Hao-Yu Yang, Johann Knechtel, Bei Yu, Evangeline F. Y. Young, Ozgur Sinanoglu

The notion of integrated circuit split manufacturing which delegates the front-end-of-line (FEOL) and back-end-of-line (BEOL) parts to different foundries, is to prevent overproduction, piracy of the intellectual property (IP), or targeted insertion of hardware Trojans by adversaries in the FEOL facility.

VLSI Mask Optimization: From Shallow To Deep Learning

no code implementations16 Dec 2019 Haoyu Yang, Wei Zhong, Yuzhe ma, Hao Geng, Ran Chen, Wanli Chen, Bei Yu

VLSI mask optimization is one of the most critical stages in manufacturability aware design, which is costly due to the complicated mask optimization and lithography simulation.

BIG-bench Machine Learning

Detecting Causal Language Use in Science Findings

no code implementations IJCNLP 2019 Bei Yu, Yingya Li, Jun Wang

We then applied the prediction model to measure the causal language use in the research conclusions of about 38, 000 observational studies in PubMed.


Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection

no code implementations25 Jun 2019 Kang Liu, Hao-Yu Yang, Yuzhe ma, Benjamin Tan, Bei Yu, Evangeline F. Y. Young, Ramesh Karri, Siddharth Garg

There is substantial interest in the use of machine learning (ML) based techniques throughout the electronic computer-aided design (CAD) flow, particularly those based on deep learning.

DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems

1 code implementation27 Dec 2018 Husheng Zhou, Wei Li, Yuankun Zhu, Yuqun Zhang, Bei Yu, Lingming Zhang, Cong Liu

Furthermore, DeepBillboard is sufficiently robust and resilient for generating physical-world adversarial billboard tests for real-world driving under various weather conditions.

Autonomous Driving DNN Testing

An Evaluation of Information Extraction Tools for Identifying Health Claims in News Headlines

no code implementations COLING 2018 Shi Yuan, Bei Yu

This study evaluates the performance of four information extraction tools (extractors) on identifying health claims in health news headlines.

Relation Extraction

A Unified Approximation Framework for Compressing and Accelerating Deep Neural Networks

no code implementations26 Jul 2018 Yuzhe Ma, Ran Chen, Wei Li, Fanhua Shang, Wenjian Yu, Minsik Cho, Bei Yu

To address this issue, various approximation techniques have been investigated, which seek for a light weighted network with little performance degradation in exchange of smaller model size or faster inference.

General Classification Image Classification +1

Recent Advances in Convolutional Neural Network Acceleration

no code implementations23 Jul 2018 Qianru Zhang, Meng Zhang, Tinghuan Chen, Zhifei Sun, Yuzhe ma, Bei Yu

We propose a taxonomy in terms of three levels, i. e.~structure level, algorithm level, and implementation level, for acceleration methods.

Image Classification

Cross-layer Optimization for High Speed Adders: A Pareto Driven Machine Learning Approach

1 code implementation18 Jul 2018 Yuzhe Ma, Subhendu Roy, Jin Miao, Jiamin Chen, Bei Yu

In spite of maturity to the modern electronic design automation (EDA) tools, optimized designs at architectural stage may become sub-optimal after going through physical design flow.

Active Learning BIG-bench Machine Learning

An NLP Analysis of Exaggerated Claims in Science News

no code implementations WS 2017 Yingya Li, Jieke Zhang, Bei Yu

The discrepancy between science and media has been affecting the effectiveness of science communication.

Misinformation Text Classification

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