Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic by NELSON L. DIAS (8078003)

“…With these practical rules, simple summation algorithms provide sufficiently robust results for the calculation of the density function and its definite integrals. …”

The experimental geometric placement adopted to assess metal artifact reduction employing the new denoising convolutional neural network metal artifact reduction hybrid reconstruct... by Tsutomu Gomi (7382183)

Subjects:

Comparisons among the denoising convolutional neural network metal artifact reduction hybrid reconstruction (DnCNN-MARHR) algorithm and the traditional reconstruction algorithms wi... by Tsutomu Gomi (7382183)

Subjects:

datasheet1_Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces.pdf by Santiago Hernández-Orozco (5070209)

datasheet2_Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces.zip by Santiago Hernández-Orozco (5070209)

datasheet1_Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces.pdf by Santiago Hernández-Orozco (5070209)

datasheet2_Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces.zip by Santiago Hernández-Orozco (5070209)

The image of the Aekley function. by Zhengyu Xu (8550660)

Differential expression analysis of the NAFLD and AIS datasets. by Junjie Su (368807)

Comparison of scores obtained by our interpenetration and scoring algorithm (ISA) and ROSETTA for a subset of structures. by Kevin Sawade (16726527)

“…However, our algorithm was 1000 times faster than pyROSETTA (both algorithms have been parallelized on a per-structure basis using the Python package joblib [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010531#pcbi.1010531.ref069" target="_blank">69</a>]).…”

Algorithm pseudocode. by Cheng-jie Chen (22272090)

“…On the basis of the Retinex model, multi-level decomposition of brightness is carried out, and different filtering parameters are set to obtain multiple illumination and reflection images with different scale information; Using exponential function and Sigmoid function to process reflection images and illumination images separately, reducing external interference on images of different scales, and solving the difficulty of enhancing images with uneven illumination, high noise, low illumination, and loss of details. …”

Mean and standard deviation of RBF classifier performance across different training algorithms with cross-validation. by Mohammad Hossein Hadizadeh Isfahani (22634016)

Mean and standard deviation of MLP classifier performance across different training algorithms with cross-validation. by Mohammad Hossein Hadizadeh Isfahani (22634016)

Comparisons of the artifact indices (AIs) determined for in-focus plane images procured via the denoising convolutional neural network metal artifact reduction hybrid reconstructio... by Tsutomu Gomi (7382183)

Subjects:

On-Demand Optimization of Colorimetric Gas Sensors Using a Knowledge-Aware Algorithm-Driven Robotic Experimental Platform by Zhehong Ai (17937324)

The “Bubblepole” (BUPO) Method for Linear-Scaling Coulomb Matrix Construction with or without Density Fitting by Frank Neese (736441)

Subjects:

Mean RMSE and R² for the training and test phases of RBF by different training algorithms for temperature and humidity prediction. by Caixia Yan (6647072)

Mean RMSE and R² for the training and test phases of MLP by different training algorithms for temperature and humidity prediction. by Caixia Yan (6647072)

Flowchart of the denoising convolutional neural network metal artifact reduction hybrid reconstruction (DnCNN-MARHR) algorithm. by Tsutomu Gomi (7382183)

Subjects:

Synthetic Realness: Authenticity as Algorithm (Reality Drift Working Paper Series, 2025) by Reality Drift Working Papers Series 2020-2025 (22445446)