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

Subjects:

Function graph and algorithm iterative graph. by WanRu Zhao (18980374)

“…However, reducing the maximum sidelobe level (SLL) of the beam pattern is a crucial challenge in antenna arrays. Pattern synthesis in smart antennas is a major area of research because of its widespread application across various radar and communication systems. …”

Algorithm results based on experimental likelihood functions. by Nicolas Herzig (9230425)

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

“…Two approaches, both leveraging batched dense linear algebra, are found to outperform the others across a suite of molecular benchmarks. We show that batched formation of the XC matrix from the density matrix yields the best performance for large (>O(103) basis functions), sparse systems such as glycine chains and water clusters. …”

Skeletonisation algorithm. by Jordan Hembrow (16908051)

Algorithm results based on FE simulated likelihood functions. by Nicolas Herzig (9230425)

“…<p>(A) Nodule depth estimation by the algorithm with the likelihood functions obtained by FEM simulation. …”

Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm by Gelio Alves (51850)

“…A major challenge in mass-spectrometry-based metaproteomics is accurately identifying and quantifying biological functions across the full taxonomic lineage of microorganisms. …”

Conservation and functional variation across TcdB subtypes. by Michael J. Mansfield (9922934)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”

EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

“…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …”

Algorithmic image feature identification. by Alex T. Keeley (16612727)

Parameters of trained algorithms. by Swathi Anil (17382903)

An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

“…<i>(b)</i> Metabolic byproducts move the relevant unperturbed state from <b>R</b>⁰ (gray ‘x’) to (black ‘x’), which is itself a function of the current environmental conditions. …”

A) Ranking of models trained on different feature sets across all tested algorithms, sorted by their F1-score. by Jose Cleydson F. Silva (8685594)

Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy by Yujin Wu (2901128)

Subjects:

Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy by Yujin Wu (2901128)

Subjects:

Maximum orientation bandwidth as a function of spatial frequency bandwidth (<i>ω</i>). by Daniel H. Baker (11559693)

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. …”

Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

Objective function values of the algorithms across individual problem instances grouped by scale: (a) Small, (b) Medium, (c) Large, (d) Super-Large. by Panfei Li (22379086)

“…<p>Objective function values of the algorithms across individual problem instances grouped by scale: (a) Small, (b) Medium, (c) Large, (d) Super-Large.…”