Sample data for <i>Neolamprologus multifasciatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Sample data for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 3 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Sample data for <i>Telmatochromis temporalis</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 4 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 1 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 2 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 5 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 6 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Memory monitoring recognition test workflow. by Pedro C. Martínez-Suárez (21192459)

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

Voice recognition workflow. by Pedro C. Martínez-Suárez (21192459)

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

Memory monitoring recognition test main screen. by Pedro C. Martínez-Suárez (21192459)

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

Task descriptions. by Pedro C. Martínez-Suárez (21192459)

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

Spherical Texture method design. by Oane Gros (20636735)

“…<b>H)</b> The <i>Spherical Texture</i> extraction is implemented as a Python package and it is directly available in <i>ilastik</i>, allowing for its adoption into the Object Classification workflow. …”

Extending the pyAFQ software. by John Kruper (18809386)

Overview of deep learning terminology. by Aaron E. Maxwell (8840882)

“…Training loops are implemented with the luz package. The geodl package provides utility functions for creating raster masks or labels from vector-based geospatial data and image chips and associated masks from larger files and extents. …”

Data from: Circadian activity predicts breeding phenology in the Asian burying beetle <i>Nicrophorus nepalensis</i> by Hao Chen (20313552)

“…</p><p dir="ltr">The dataset includes:</p><ol><li>Raw locomotor activity measurements (.txt files) with 1-minute resolution</li><li>Breeding experiment data (Pair_breeding.csv) documenting nest IDs, population sources, photoperiod treatments, and breeding success</li><li>Activity measurement metadata (Loc_metadataset.csv) containing detailed experimental parameters and daily activity metrics extracted using tsfresh</li></ol><p dir="ltr">The repository also includes complete analysis pipelines implemented in both Python (3.8.8) and R (4.3.1), featuring:</p><ul><li>Data preprocessing and machine learning model development</li><li>Statistical analyses</li><li>Visualization scripts for generating Shapley plots, activity pattern plots, and other figures</li></ul><p></p>…”

Linking Thermal Conductivity to Equations of State Using the Residual Entropy Scaling Theory by Zhuo Li (165589)

“…To use our model easily, a software package written in Python is provided in the Supporting Information.…”

Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games" by Krishnendu Chatterjee (15367413)

“…</p><p dir="ltr">To run each of the experiments, simply execute: <code>python3 [experiment file]</code> where <code>[experiment file]</code> is one of (ii), (iii) or (iv) from the above list.…”

adnus by Mehmet Keçeci (14301782)

“…<p dir="ltr">adnus (AdNuS): Advanced Number Systems</p><p dir="ltr">adnus is a Python library that provides an implementation of various advanced number systems. …”