Spatiotemporal Soil Erosion Dataset for the Yarlung Tsangpo River Basin (1990–2100) by peng xin (21382394)

“…Bias correction was conducted using a 25-year baseline (1990–2014), with adjustments made monthly to correct for seasonal biases. The corrected bias functions were then applied to adjust the years (2020–2100) of daily rainfall data using the "ibicus" package, an open-source Python tool for bias adjustment and climate model evaluation. …”

NanoDB: Research Activity Data Management System by Lorenci Gjurgjaj (19702207)

“…Cross-Platform Compatibility: Works on Windows, macOS, and Linux. In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …”

Code and Data for 'Fabrication and testing of lensed fiber optic probes for distance sensing using common path low coherence interferometry' by Radu Stancu (21165068)

“…Distance Sensing</p><p dir="ltr">Code and data to demonstrate extracting distance sensing data from A-scans and to generate Fig. 8 using the algorithm described in Fig. 7. Functions to generate distance measurements are in 'distance_sensing_utilities.py' and an example of how to use this on data in the 'data' folder is in 'distance_sensing_example.py', which generates Fig 8. …”

Graphical representation of the optimization process in machine learning, focusing on the adjustment of weights during gradient descent. by Liu Liu (512237)

“…The curve shows how the cost function decreases to reach a global minimum <i>J</i>_min(<i>w</i>), indicating the optimal weight where the cost function reaches its minimum. …”

Bayesian nonparametric mixture of experts for inverse problems by TrungTin Nguyen (20389663)

“…We establish posterior consistency for the number of mixture components after the merge-truncate-merge algorithm post-processing. Illustrations on simulated data show good results in terms of recovering the true number of experts and the regression function.…”

Conditional probability tensor decompositions for multivariate categorical response regression by Aaron J. Molstad (5243561)

“…<p>In many modern regression applications, the response consists of multiple categorical random variables whose probability mass is a function of a common set of predictors. In this article, we propose a new method for modeling such a probability mass function in settings where the number of response variables, the number of categories per response, and the dimension of the predictor are large. …”

Code by Baoqiang Chen (21099509)

“…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”

Core data by Baoqiang Chen (21099509)

“…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”

Brain-in-the-Loop Learning for Intelligent Vehicle Decision-Making by Xiaofei Zhang (16483224)

“…In this paper, we utilize functional near-infrared spectroscopy (fNIRS) signals as real-time human risk-perception feedback to establish a brain-in-the-loop (BiTL) trained artificial intelligence algorithm for decision-making. …”

Network visualization. by Amina Azaiez (20623488)

“…Colors refer to clusters obtained using the Louvain clustering algorithm with the Barber [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0311626#pone.0311626.ref033" target="_blank">33</a>] modularity function. …”

Landscape17 by Vlad Carare (22092515)

“…In particular, the explicit inclusion of transition states, which are more difficult to characterise using standard molecular dynamics, allows for assessment of global kinetics and comparison of MLIP landscapes with the DFT reference.</p><h3>Density functional theory calculations</h3><p dir="ltr">The reference potential energy landscapes were computed using density functional theory with the ωB97x hybrid-energy exchange correlation functional and a 6-31G(d) basis set within Psi4. …”

Dual-Level Parametrically Managed Neural Network Method for Learning a Potential Energy Surface for Efficient Dynamics by Suman Bhaumik (14094200)

“…The goal of the present work is to remedy this by a low-cost method for incorporating well understood features of potential energy surfaces into an efficient data-driven machine learning algorithm. Our focus is on regions where conventional surface fitting does not need large amounts of accurate data, in particular, geometries with large separations of subsystems–where it is well recognized that the potential should reach its asymptotic form–and geometries with very close atoms–where the potential should be repulsive enough to prevent trajectories from reaching classically inaccessible regions but need not be highly quantitative. …”

Nonparametric Distribution Regression and Change Point Detection in High-Dimensions by Shivam Kumar (17808571)

“…First, we introduce the Functional Regression Binary Segmentation (FRBS) algorithm for change-point detection in the slope function when predictors are functions and responses are scalars. …”

Instances and detailed results of the paper <i>Stochastic scheduling on a restricted batching machine</i> by Yasmin Rios Solis (3909469)

“…We consider minimizing the maximum lateness under uncertainty on the processing time of jobs. This function is particularly relevant in manufacturing environments where these machines are present, as meeting due dates is crucial on these bottleneck machines. …”

Robust Matrix Completion with Heavy-Tailed Noise by Bingyan Wang (275853)

“…<p>This article studies noisy low-rank matrix completion in the presence of heavy-tailed and possibly asymmetric noise, where we aim to estimate an underlying low-rank matrix given a set of highly incomplete noisy entries. …”

Parameter estimates of mixed generalized Gaussian distribution for modelling the increments of electroencephalogram data by Zoe Salinger (19090613)

“…</p><p>The parameters of this distribution were estimated using the expectation-maximization algorithm, where the added shape parameter is estimated using the higher order statistics approach based on an analytical relationship between the shape parameter and kurtosis.…”

<b>Fig. 6 |</b> <b>Autonomous microrobot navigation upstream in a flow environment.</b> by Mahmoud Medany (20766911)

“…</b> Schematic of the reward function adjustment to promote microrobot navigation close to the wall, minimizing drag. …”

Mechanomics Code - JVT by Carlo Vittorio Cannistraci (5854046)

“…The functions were tested respectively in: MATLAB 2018a or youger, Python 3.9.4, R 4.0.3.…”

Simulated and Field-Based Error Characterisation of Animal Geolocalisation and Relative Positioning via Commercial Drones by Kilian Meier (22303138)

“…</i></b></p><p dir="ltr">Drones can be used for wildlife monitoring, specifically, to monitor the absolute location and relative position of individuals, which can be achieved with commercial drones using a monoplotting algorithm. The accuracy of the localisation processes has been characterised as a function of distance and elevation from the point of interest (POI) to inform field deployment and experiment design using this method. …”

Table 1_Kefir and healthy aging: revealing thematic gaps through AI-assisted screening and semantic evidence mapping.docx by Francesco Chiani (2661328)

“…To overcome this fragmentation, we applied an integrative approach that combines a cutting-edge AI-assisted algorithm for evidence screening with a Python-based semantic clustering pipeline. …”