EALM algorithm. حسب Weibo Wang (782424)

Overview of the algorithm used to calculate Lyapunov exponents for assessing the stability and chaotic behavior of dynamical systems. حسب Adil Jhangeer (9711917)

Implementation algorithm. حسب Michael A. Colman (7163735)

Final assignment algorithm. حسب Negin Alisoltani (11949357)

Empirical cumulative distribution function of RMSE for three sources. حسب Nauman Ahmed (8086868)

Empirical cumulative distribution function of RMSE for two sources. حسب Nauman Ahmed (8086868)

Empirical cumulative distribution function of RMSE for four sources. حسب Nauman Ahmed (8086868)

Optimized algorithm framework diagram. حسب Xutao Liu (13006965)

الموضوعات:

The SSIM for the different algorithms. حسب Bingbing Li (461702)

"…The mean square error decreased by 0.10dB. When using the algorithm for denoising, the research method had a minimum denoising time of only 13ms, which saved 9ms and 3ms compared to the hard threshold algorithm (Hard TA) and soft threshold algorithm (Soft TA), respectively. …"

Ridge wave transformation flowchart. حسب Bingbing Li (461702)

"…The mean square error decreased by 0.10dB. When using the algorithm for denoising, the research method had a minimum denoising time of only 13ms, which saved 9ms and 3ms compared to the hard threshold algorithm (Hard TA) and soft threshold algorithm (Soft TA), respectively. …"

Gillespie algorithm simulation parameters. حسب Nicholas H. Vitale (20469289)

"…Both the ensemble and stochastic models presented in this work have been verified using Monte Carlo molecular dynamic simulations that utilize the Gillespie algorithm. …"

Two-stage object detection algorithm process. حسب Xutao Liu (13006965)

الموضوعات:

Block ridge wave denoising flowchart. حسب Bingbing Li (461702)

"…The mean square error decreased by 0.10dB. When using the algorithm for denoising, the research method had a minimum denoising time of only 13ms, which saved 9ms and 3ms compared to the hard threshold algorithm (Hard TA) and soft threshold algorithm (Soft TA), respectively. …"

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

The real NGD values, one-step ahead training set predictions, and multi-step ahead test set predictions using the AI-AFTER algorithm for Kayseri. حسب Burak Alakent (463512)

The optimal contact/quarantine rates from the family of functions (4) and (5) for Hainan and Xinjiang. حسب Mengqi He (5753525)

الموضوعات:

The optimal contact/quarantine rates from the family of functions (4) and (5) for Xi’an, Guangzhou and Yangzhou. حسب Mengqi He (5753525)

الموضوعات:

Supplementary file 1_Predicting the onset of internalizing disorders in early adolescence using deep learning optimized with AI.zip حسب Nina de Lacy (6559520)

"…Introduction<p>Internalizing disorders (depression, anxiety, somatic symptom disorder) are among the most common mental health conditions that can substantially reduce daily life function. Early adolescence is an important developmental stage for the increase in prevalence of internalizing disorders and understanding specific factors that predict their onset may be germane to intervention and prevention strategies.…"

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

"…We investigate the shape of a discrete algorithmic space when performing regression or classification using a loss function parametrized by algorithmic complexity, demonstrating that the property of differentiation is not required to achieve results similar to those obtained using differentiable programming approaches such as deep learning. …"

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

"…We investigate the shape of a discrete algorithmic space when performing regression or classification using a loss function parametrized by algorithmic complexity, demonstrating that the property of differentiation is not required to achieve results similar to those obtained using differentiable programming approaches such as deep learning. …"