Search Results for author: Jun Feng

Found 23 papers, 4 papers with code

Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules

no code implementations8 Jan 2024 Joseph C. Kim, David Bloore, Karan Kapoor, Jun Feng, Ming-Hong Hao, Mengdi Wang

We demonstrate that standard architectures and training strategies, such as maximum likelihood alone, fail while our novel architecture and multi-stage training strategy are able to model the conformational distributions of protein G and HP35.

Invariant Content Synergistic Learning for Domain Generalization of Medical Image Segmentation

no code implementations5 May 2022 Yuxin Kang, Hansheng Li, Xuan Zhao, Dongqing Hu, Feihong Liu, Lei Cui, Jun Feng, Lin Yang

In this paper, we propose a method, named Invariant Content Synergistic Learning (ICSL), to improve the generalization ability of DCNNs on unseen datasets by controlling the inductive bias.

Domain Generalization Image Segmentation +4

ScalingNet: extracting features from raw EEG data for emotion recognition

no code implementations7 Feb 2021 Jingzhao Hu, Chen Wang, Qiaomei Jia, Qirong Bu, Jun Feng

Convolutional Neural Networks(CNNs) has achieved remarkable performance breakthrough in a variety of tasks.

EEG Electroencephalogram (EEG) +1

Lookup subnet based Spatial Graph Convolutional neural Network

no code implementations4 Feb 2021 Jingzhao Hu, Xiaoqi Zhang, Qiaomei Jia, Chen Wang, Qirong Bu, Jun Feng

Convolutional Neural Networks(CNNs) has achieved remarkable performance breakthrough in Euclidean structure data.

Stream-Flow Forecasting of Small Rivers Based on LSTM

no code implementations16 Jan 2020 Youchuan Hu, Le Yan, Tingting Hang, Jun Feng

Stream-flow forecasting for small rivers has always been of great importance, yet comparatively challenging due to the special features of rivers with smaller volume.

Time Series Time Series Analysis

Visual cryptography in single-pixel imaging

no code implementations12 Nov 2019 Shuming Jiao, Jun Feng, Yang Gao, Ting Lei, Xiaocong Yuan

The secret image can be recovered when identical illumination patterns are projected onto multiple visual key images and a single detector is used to record the total light intensities.

Does deep learning always outperform simple linear regression in optical imaging?

no code implementations31 Oct 2019 Shuming Jiao, Yang Gao, Jun Feng, Ting Lei, Xiaocong Yuan

Despite the success, the limitations and drawbacks of deep learning in optical imaging have been seldom investigated.


Multi-Kernel Filtering for Nonstationary Noise: An Extension of Bilateral Filtering Using Image Context

no code implementations17 Aug 2019 Feihong Liu, Jun Feng, Pew-Thian Yap, Dinggang Shen

Next, a leaf cluster is used to generate one of the multiple kernels, and two corresponding predecessor clusters are used to fine-tune the adopted kernel.

Clustering Denoising +1

DeepBundle: Fiber Bundle Parcellation with Graph Convolution Neural Networks

no code implementations7 Jun 2019 Feihong Liu, Jun Feng, Geng Chen, Ye Wu, Yoonmi Hong, Pew-Thian Yap, Dinggang Shen

GCNNs are capable of extracting the geometric features of each fiber tract and harnessing the resulting features for accurate fiber parcellation and ultimately avoiding the use of atlases and any registration method.

Optical machine learning with incoherent light and a single-pixel detector

no code implementations24 Apr 2019 Shuming Jiao, Jun Feng, Yang Gao, Ting Lei, Zhenwei Xie, Xiaocong Yuan

Like an optical computer, the system can perform machine learning tasks such as number digit recognition in an all-optical manner.

BIG-bench Machine Learning

Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning

no code implementations17 Sep 2018 Jun Feng, Heng Li, Minlie Huang, Shichen Liu, Wenwu Ou, Zhirong Wang, Xiaoyan Zhu

The first one is lack of collaboration between scenarios meaning that each strategy maximizes its own objective but ignores the goals of other strategies, leading to a sub-optimal overall performance.

Multi-agent Reinforcement Learning reinforcement-learning +1

Reinforcement Learning for Relation Classification from Noisy Data

2 code implementations24 Aug 2018 Jun Feng, Minlie Huang, Li Zhao, Yang Yang, Xiaoyan Zhu

In this paper, we propose a novel model for relation classification at the sentence level from noisy data.

Classification reinforcement-learning +3

Design of optimal illumination patterns in single-pixel imaging using image dictionaries

no code implementations4 Jun 2018 Jun Feng, Shuming Jiao, Yang Gao, Ting Lei, Xiaocong Yuan

Single-pixel imaging (SPI) has a major drawback that many sequential illuminations are required for capturing one single image with long acquisition time.

GAKE: Graph Aware Knowledge Embedding

1 code implementation COLING 2016 Jun Feng, Minlie Huang, Yang Yang, Xiaoyan Zhu

Knowledge embedding, which projects triples in a given knowledge base to d-dimensional vectors, has attracted considerable research efforts recently.

Knowlege Graph Embedding by Flexible Translation

no code implementations20 May 2015 Jun Feng, Mantong Zhou, Yu Hao, Minlie Huang, Xiaoyan Zhu

TransF regards relation as translation between head entity vector and tail entity vector with flexible magnitude.

General Classification Knowledge Graph Embedding +4

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