Table4_Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.XLSX by Lei Chen (54296)

“…The computational prediction of protein subcellular localizations can be performed on the basis of the sequence and the functional characteristics. …”

Table1_Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.XLSX by Lei Chen (54296)

“…The computational prediction of protein subcellular localizations can be performed on the basis of the sequence and the functional characteristics. …”

The optimal solution set of NYN by using different algorithms. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

The optimal solution set of HN by using different algorithms. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz by Faizan Ali (21689861)

Subjects:

Types of training algorithms. by Caixia Yan (6647072)

Convergence curves of various algorithms under test functions. by Jiayuan Wang (3765376)

Convergence curves of various algorithms under test functions. by Jiayuan Wang (3765376)

The convergence curve of each optimization algorithm under the test function. by Hao Yang (328526)

gmxapi usage examples. by M. Eric Irrgang (4487278)

Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional by Ryan Stocks (16867476)

“…In this work, we present a comparative study of four GPU-accelerated algorithms for evaluating the KS-DFT exchange–correlation (XC) potential with an atom-centered Gaussian basis. …”

Python scripts used to model CPU errors by Poisson distribution density mass function and to draw graph of Poisson events (needs Matplot, SciPy, PysimpleGUI and NumPy) by Santhosh Kumar Rajamani (13023678)

Model training accuracy for Random Forest (RF), Multilayer Perceptron (MLP), and Radial Basis Function (RBF) algorithms by adding variables based on the correlation results. by Mohsen Yoosefzadeh-Najafabadi (6917399)

Testing performance comparison for different algorithms. by Roberto Bárcenas (13924220)

Training performance comparison for different algorithms. by Roberto Bárcenas (13924220)

In this example the MPC algorithm perfectly tracks the noisy signal , which results in many false spikes. by Nicholas A. Rondoni (21573261)

Verification of the in-line PS function. by Raul Castañeda (13932971)

Available functions in the utility package. by Raul Castañeda (13932971)

The SVM objective function minimization against iterations. by Ali Ahmed (2567584)

Subjects:

Locally sparse function-on-function regression by Mauro Bernardi (418110)

“…To balance these two extremes, we propose a locally sparse functional regression model in which the functional regression coefficient is allowed (but not forced) to be exactly zero for a subset of its domain. …”