Data and code resources. by Sam Hall-McMaster (10343795)

“…This activation had a functional connection to behavior in that stronger activation of SF&GPI solutions in visual areas was associated with increased behavioral reuse. These findings point to a possible neural implementation of an adaptive algorithm for generalization across tasks.…”

The folder containing the code is provided as supportive documentation associated with this paper. by Quxi Kuang (22493270)

Subjects:

Mesh Division Schematic Diagram. by Nan Ru (9594384)

K-shortest path algorithm, finding count, and OD algorithm. by Jin Ki Eom (21192426)

Automatic generation of mesh diagrams. by Ronghua Meng (20978441)

Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code by Goutami Sooda (20714729)

A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

a. How various statistical models account for modulation classification performance across the entire dataset. by Chris Scholes (3309477)

The FEM mesh model for the three-layer case, where 7919 degrees of freedom are used. by Xiaogang Li (299205)

Parameters of ML algorithms. by Md. Maeen Molla (20827041)

Algorithm testing. by Ziad M. Ali (12516532)

Subjects:

XGBoost odor prediction model: finding the structure-odor relationship of odorant molecules using the extreme gradient boosting algorithm by Pankaj Tyagi (20147683)

The parameter setting of the evolutionary neural network. by Wenbing Shi (5806160)

Subjects:

The genome coding scheme. by Wenbing Shi (5806160)

Subjects:

UAV target finding and target tracking. by Yuanhong Dan (20570631)

UAV target finding and target tracking. by Yuanhong Dan (20570631)

Model comparison between our model-free algorithm (here MF*) and SARSA. by Carlos A. Velázquez-Vargas (19751567)

Code used for data analysis in this study. by Nourin Sultana (22339463)

Subjects:

Multi-material topology optimization using scaled boundary finite element method by Mohammed Saif Zamiruddin Siddiqui (22384884)

“…SBFEM is implemented and its performance is tested across different density interpolation-based MMTO methods: the Alternating Active-Phase (AAP) algorithm, SIMP with mapping based interpolation, and polygonal mesh based MMTO, PolyMat which uses Discrete Material Optimization (DMO) combined with Zhang–Paulino–Ramos (ZPR) update scheme. …”

Research data for paper: Efficient Event-based Delay Learning in Spiking Neural Networks by Balázs Mészáros (16890225)

“…Our method supports multiple spikes per neuron and introduces a delay learning algorithm that can, in contrast to previous methods, also be applied to recurrent Spiking Neural Networks. …”