A Practical Algorithm to Solve the Near-Congruence Problem for Rigid Molecules and Clusters by José Manuel Vásquez-Pérez (12843737)

“…The Fortran implementation of the algorithm is available as an open source library (https://github.com/qcuaeh/molalignlib) and is suitable to be used in global optimization methods for the identification of local minima or basins.…”

Comparison of ranks for classification algorithms across performance metrics. by Stephen R. Piccolo (8367780)

Image 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.tif by Xuehui Fan (10762662)

Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx by Xuehui Fan (10762662)

Data Sheet 5_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 8_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 6_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 3_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 4_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

“…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”

DataSheet1_Towards Computational Modeling of Human Goal Recognition.pdf by Shify Treger (11973125)

“…Moreover, the proposed algorithm marries rationality-based and plan-library based methods seamlessly.…”

DataSheet1_Towards Computational Modeling of Human Goal Recognition.pdf by Shify Treger (11973125)

“…Moreover, the proposed algorithm marries rationality-based and plan-library based methods seamlessly.…”

hIPPYlib: An Extensible Software Framework for Large-scale Inverse Problems by Olalekan A. Babaniyi (767286)

“…We present an Inverse Problem PYthon library (hIPPYlib) for solving large-scale deterministic and Bayesian inverse problems governed by partial differential equations (PDEs). hIPPYlib implements state-of-the-art scalable algorithms that exploit the structure of the problem, notably the Hessian of the log posterior. …”

COSMO-Bench by Daniel McGann (18759496)

“…To address this gap we design and release the Collaborative Open-Source Multi-robot Optimization Benchmark (COSMO-Bench) -- a suite of 24 datasets derived from a state-of-the-art C-SLAM front-end and real-world LiDAR data</p><p dir="ltr">This entry, hosted through Carnegie Mellon University libraries, serves to host the official dataset release in perpetuity. …”

Table_3_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx by Qian Wang (32718)

“…Here, we present the G2P container developed for the Singularity platform, which not only contains a library of 16 state-of-the-art GS models and 13 evaluation metrics. …”

Image_1_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg by Qian Wang (32718)

“…Here, we present the G2P container developed for the Singularity platform, which not only contains a library of 16 state-of-the-art GS models and 13 evaluation metrics. …”

Image_2_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg by Qian Wang (32718)

“…Here, we present the G2P container developed for the Singularity platform, which not only contains a library of 16 state-of-the-art GS models and 13 evaluation metrics. …”