SHAP summary plot. حسب Meng Cao (105914)

"…The optimal model was further assessed for predictor importance utilizing the SHAP method and deployed on a web platform using the Streamlit library.…"

Display of the web prediction interface. حسب Meng Cao (105914)

"…The optimal model was further assessed for predictor importance utilizing the SHAP method and deployed on a web platform using the Streamlit library.…"

Presentation_1_Optimization of the k-nearest-neighbors model for summer Arctic Sea ice prediction.pdf حسب Yongcheng Lin (776525)

"…Based on the physical characteristics of summer sea ice, different algorithms are employed to optimize the prediction model. …"

Presentation_1_Optimization of the k-nearest-neighbors model for summer Arctic Sea ice prediction.pdf حسب Yongcheng Lin (776525)

"…Based on the physical characteristics of summer sea ice, different algorithms are employed to optimize the prediction model. …"

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. حسب Jiaqing Luo (10975030)

"…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …"

Parameter settings. حسب Yang Cao (53545)

"…<div><p>Differential Evolution (DE) is widely recognized as a highly effective evolutionary algorithm for global optimization. It has proven its efficacy in tackling diverse problems across various fields and real-world applications. …"

Portable Library for Homomorphic Encrypted Machine Learning on FPGA Accelerated Cloud Cyberinfrastructure حسب Zhihan Xu (17049357)

"…This project will leverage our novel algorithmic, architectural, and memory optimizations on FPGAs to develop a portable library to enable secure and trustworthy ML inference. …"

Portable Library for Homomorphic Encrypted Machine Learning on FPGA Accelerated Cloud Cyberinfrastructure حسب Zhihan Xu (17049357)

"…This project will leverage our novel algorithmic, architectural, and memory optimizations on FPGAs to develop a portable library to enable secure and trustworthy ML inference. …"

An exemplar procedure for activity flow modeling based on the direct and shortest paths at a network density of 15%. حسب Zhengdong Wang (35299)

Acceleration of Inverse Molecular Design by Using Predictive Techniques حسب Jos L. Teunissen (1911856)

"…This study addresses one of the most important drawbacks inherently related to molecular searches in chemical compound space by greedy algorithms such as Best First Search and Genetic Algorithm, i.e., the large computational cost required to optimize one or more quantum-chemical properties. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"