Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

Both Ankle fNIRS MI dataset by Hammad Gilani (8060012)

“…<br></li></ul><p dir="ltr">This dataset can be used to explore neural signatures of lower limb motor imagery, develop brain-computer interface (BCI) algorithms, and investigate cortical hemodynamics associated with motor planning and control.…”

Both Knees fNIRS MI dataset by Hammad Gilani (8060012)

“…<br></li></ul><p dir="ltr">This dataset can be used to explore neural signatures of lower limb motor imagery, develop brain-computer interface (BCI) algorithms, and investigate cortical hemodynamics associated with motor planning and control.…”

ABIDE dataset subject demographics. by Alexandria M. Jensen (6494957)

Subjects:

Generated blended data using mouse brain cells and human embryonic heart cells, labeled as <i>Mix</i>[<i>a</i>,<i>b</i>,<i>c</i>], indicates the proportion of mouse brain cells fou... by Nuray Sogunmez Erdogan (21533872)

Analysis of ABIDE dataset: Conventional regression frameworks for optimized algorithmic value. by Alexandria M. Jensen (6494957)

Subjects:

Results from different ML algorithms. by Caroline L. Alves (14271413)

ROC curve for each ML algorithm. by Caroline L. Alves (14271413)

Distribution of cross correlations in functional connectivity in ABIDE sample. by Alexandria M. Jensen (6494957)

Subjects:

Confusion matrices depict the performance of various ML algorithms. by Caroline L. Alves (14271413)

Precise spatial delineation of brain cell types in adult mouse brain. by Nuray Sogunmez Erdogan (21533872)

Acurracy comparison of CCA and FBCCA algorithms. by Hossein Hamidi Shishavan (19688384)

Summary of the contrasts obtained from the normalized images for both inclusions as a function of the host type and the wavelength. by María Victoria Waks-Serra (21578611)

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

Studies with ML classification algorithms for distinguishing ASD and ADHD groups described in subsection 1.2. by Caroline L. Alves (14271413)

Evolution of the rescaled hydraulic diameter () and complexity () in both simulations and seal tomograms as a function of simulation timestep and relative age (). by Jonathan E Kings (20818367)

The ALO algorithm optimization flowchart. by Wenjing Wang (181404)

“…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …”

The IALO algorithm solution flowchart. by Wenjing Wang (181404)

“…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …”

Reverse engineering information flow using stimulus-encoding and stimulus-transfer estimation algorithms. by Gabriel Matías Lorenz (21094672)

Classification accuracy as a function of the amount of training data. by Dovilė Kurmanavičiūtė (21072549)