A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data by Anthony S. Barente (14035175)

Subjects:

Results of DE algorithms with our scheme and original DE algorithms when function dimensionality is set 100. by Haiming Du (6691646)

Results of DE algorithms with our scheme and original DE algorithms when function dimensionality is set 30. by Haiming Du (6691646)

Results of DE algorithms with our scheme and original DE algorithms when function dimensionality is set 50. by Haiming Du (6691646)

Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements by Pascal Wang (10130612)

“…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …”

Rosetta energy functions for membrane proteins cannot identify the inward-facing conformation of PfMATE. by Diego del Alamo (9925083)

Loss function value changes in CNN training changes with epochs for both training dataset and testing dataset. by Jiaxi Wang (545353)

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)

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Total number of cells in each region, per brain, projecting to layer 2/3 neurons in primary visual cortex. by Adam L. Tyson (10892822)

Illustration of the cell detection process. by Adam L. Tyson (10892822)

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

Comparison of details of different algorithms. by Hao Wu (65943)

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Structure of the LMPEC algorithm model. by Hao Wu (65943)

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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)

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

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

500 <i>ϕ</i> vectors learned from <i>ℓ</i>_1/2 thresholding. by Ilias Rentzeperis (10215602)

“…Traditionally, to replicate such biological sparsity, generative models have been using the <i>ℓ</i>₁ norm as a penalty due to its convexity, which makes it amenable to fast and simple algorithmic solvers. …”

Sensitivity of the system with respect to variation of l 2% of the functions . by Mario Saviano (17389551)