Yanfu Zhang

Williams (United States)

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Heng Huang

University of Maryland, College Park

Shangqian Gao

University of Pittsburgh

Runxue Bao

University of Pittsburgh

Liang Zhan

University of Pittsburgh

Sebastian Scherer

Carnegie Mellon University

Paul M. Thompson

University of Southern California

Rogerio Bonatti

Microsoft (United States)

Wenshan Wang

Carnegie Mellon University

Feng Zheng

Southern University of Science and Technology

Zhepeng Wang

Wuhan University of Technology

Cooperative Institutions

University of Pittsburgh

Chinese Academy of Sciences

North China Electric Power University

University of Chinese Academy of Sciences

Sun Yat-sen University

Shanghai Jiao Tong University

Tsinghua University

University of California, San Francisco

Carnegie Mellon University

University of Electronic Science and Technology of China

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

HazeRD: An outdoor scene dataset and benchmark for single image dehazing

2022 IEEE International Conference on Image Processing (ICIP) (2017)

Yanfu Zhang Li Ding Gaurav Sharma

In this paper, a new dataset, HazeRD, is proposed for benchmarking dehazing algorithms under more realistic haze conditions. HazeRD contains fifteen real outdoor scenes, for each of which five different weather conditions are simulated. As opposed to prior datasets that made use of synthetically generated images or indoor images with unrealistic parameters for haze simulation, our outdoor dataset allows for more realistic simulation of haze with parameters that are physically realistic and justified by scattering theory. All images are of high resolution, typically six to eight megapixels. We test the performance of several state-of-the-art dehazing techniques on HazeRD. The results exhibit a significant difference among algorithms across the different datasets, reiterating the need for more realistic datasets such as ours and for more careful benchmarking of the methods.

Benchmarking

Benchmark (surveying)

Haze

10.1109/icip.2017.8296874

Cite

Citations (224)

LitGene: a transformer-based model that uses contrastive learning to integrate textual information into gene representations

bioRxiv (Cold Spring Harbor Laboratory) (2024)

Ala Jararweh Oladimeji Macaulay David Arredondo Olufunmilola Oyebamiji Yue Hu

Abstract Representation learning approaches leverage sequence, expression, and network data, but utilize only a fraction of the rich textual knowledge accumulated in the scientific literature. We present LitGene, an interpretable transformer-based model that refines gene representations by integrating textual information. The model is enhanced through a Contrastive Learning (CL) approach that identifies semantically similar genes sharing a Gene Ontology (GO) term. LitGene demonstrates accuracy across eight benchmark predictions of protein properties and robust zero-shot learning capabilities, enabling the prediction of new potential disease risk genes in obesity, asthma, hypertension, and schizophrenia. LitGene’s SHAP-based interpretability tool illuminates the basis for identified disease-gene associations. An automated statistical framework gauges literature support for AI biomedical predictions, providing validation and improving reliability. LitGene’s integration of textual and genetic information mitigates data biases, enhances biomedical predictions, and promotes ethical AI practices by ensuring transparent, equitable, open, and evidence-based insights. LitGene code is open source and also available for use via a public web interface at litgene.avisahuai.com .

10.1101/2024.08.07.606674

Cite

Citations (0)

Demystify the Gravity Well in the Optimization Landscape (Student Abstract)

Proceedings of the AAAI Conference on Artificial Intelligence (2023)

Jason Dou Runxue Bao SUSAN L. SONG Shuran Yang Yanfu Zhang

We provide both empirical and theoretical insights to demystify the gravity well phenomenon in the optimization landscape. We start from describe the problem setup and theoretical results (an escape time lower bound) of the Softmax Gravity Well (SGW) in the literature. Then we move toward the understanding of a recent observation called ASR gravity well. We provide an explanation of why normal distribution with high variance can lead to suboptimal plateaus from an energy function point of view. We also contribute to the empirical insights of curriculum learning by comparison of policy initialization by different normal distributions. Furthermore, we provide the ASR escape time lower bound to understand the ASR gravity well theoretically. Future work includes more specific modeling of the reward as a function of time and quantitative evaluation of normal distribution’s influence on policy initialization.

Initialization

Phenomenon

10.1609/aaai.v37i13.26961

Cite

Citations (4)

Analysis on principle and key techniques of deterministic finishing

Yanfu Zhang Bo Wang Shen Dong

Soft finishing methods are required to meet the need of modern optical surface while the deterministic finishing processing is needed to ensure the high precession surface.. The concepts and the math model of deterministic finishing are presented. The key technologies of deterministic finishing are analyzed, which include the requirement of removal rate function, the solving method of dwell time, and the finishing scan path. The deterministic finishing methods used at present are Small Tool Lapping and Polishing (STLP), Magneto-Rheological Finishing (MRF), Ion Beam Figuring (IBF), Atmospheric Pressure Plasma Chemical Finishing (APPCF) and so on. The principle, removal rate function characteristic and new development of these deterministic finishing methods are introduced.

Lapping

Figuring

Dwell time

Surface finishing

10.1109/mace.2011.5987851

Cite

Citations (0)

Operation optimization of regional integrated energy system based on the modeling of electricity-thermal-natural gas network

Applied Energy (2019)

Yongli Wang Yudong Wang Yujing Huang Jiale Yang Yuze Ma

Energy system

Electricity system

Thermal energy

10.1016/j.apenergy.2019.113410

Cite

Citations (200)

Integrating Heterogeneous Brain Networks for Predicting Brain Disease Conditions

Lecture notes in computer science (2019)

Yanfu Zhang Liang Zhan Weidong Cai Paul M. Thompson Heng Huang

Pooling

Identification

10.1007/978-3-030-32251-9_24

Cite

Citations (25)

Morphological and anatomical structural observation of stems and leaves of eight species of Calymperaceae in Hainan.

Guangxi Zhiwu / Guihaia (2019)

Sha Wei Lili Liu Tianyi Ma Yanfu Zhang Meijuan Zhang

Source

Cite

Citations (0)

TOPSIS Method Based on Entropy Weight for Supplier Evaluation of Power Grid Enterprise

Advances in Social Science, Education and Humanities Research/Advances in social science, education and humanities research (2015)

Yanfu Zhang

Demand for electric power material has timeliness and effectiveness. To ensure material demands are timely supplied, screening providers need to be cautious. This paper will apply Entropy Weight method and TOPSIS method to building a model for supplier evaluation of Power Grid Enterprise, and verifies by an example.

TOPSIS

Power grid

10.2991/ermm-15.2015.88

Cite

Citations (22)

Auto- Train-Once: Controller Network Guided Automatic Network Pruning from Scratch

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024)

Xidong Wu Shangqian Gao Zeyu Zhang Zhenzhen Li Runxue Bao

Scratch

Pruning

10.1109/cvpr52733.2024.01530

Cite

Citations (1)

The Research of Customer Relationship Management of Power Supply Enterprises

Yanfu Zhang Lu Ye

The power supply enterprises face much greater pressure caused by external environment and fierce competition pressure caused by the alternative energy sources after reform. These all request the power supply enterprises to introduce the customer relationship management idea as soon as possible. Through which they can discover the effective solutions from the customers' feedback. Analyzing the common issue existing in the power enterprise marketing work. Putting forward the method of practicing CRM through marketing idea innovation and receiving assistance of the modern management system. Strengthen the customer relationship management is the effective method to integrate the enterprise resources, promote the very core competitive ability of the enterprise and realize the sustainable development. It is of great importance to help the electric power enterprise sets up the good public brand image and establish mutually pleasant faithful relation between the enterprise and its customers at the same time.

Customer Relationship Management

Enterprise life cycle

10.1109/icpst.2006.321460

Cite

Citations (6)