A hybrid algorithm based on improved threshold function and wavelet transform. by Bingbing Li (461702)

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

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

Performance of the greedy approximation algorithm. by Virgile Andreani (17087764)

Subjects: “…unlike approximation algorithms…”

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. …”

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…</p><p dir="ltr">The package includes:</p><ul><li>Scripts for first-order analysis, third-order modeling, optimization using a Physically Grounded Merit Function (PGMF), and RMS-based refinement.</li><li>A subfolder named <b>Images</b>, which stores the figures generated by six of the seven provided scripts.…”

Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

Frequency of binding site usage as a function of binding site length. by Virgile Andreani (17087764)

Subjects: “…unlike approximation algorithms…”

500 <i>ϕ</i> vectors learned from hard 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. In this work, we use biological vision as a test-bed and show that the soft thresholding operation associated to the use of the <i>ℓ</i>₁ norm is highly suboptimal compared to other functions suited to approximating <i>ℓ</i>_<i>p</i> with 0 ≤ <i>p</i> < 1 (including recently proposed continuous exact relaxations), in terms of performance. …”

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

Policy network (<i>θ</i>′) of SAM to accommodate PPO algorithm. by Zhenhan Huang (12107002)

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

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Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined. by Yuanchen Zhao (12905580)

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

The improved Hard TA and Soft TA. by Bingbing Li (461702)

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The diagram of Hard TA and Soft TA. by Bingbing Li (461702)

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Box plot of the algorithms based on 12 benchmark functions. by Chuang Zhang (2199421)

“…<p>Box plot of the algorithms based on 12 benchmark functions.</p>…”

Convergence behavior of the algorithms based on 12 benchmark functions. by Chuang Zhang (2199421)

“…<p>Convergence behavior of the algorithms based on 12 benchmark functions.</p>…”

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