This repo contains the research project submissions for the BeyondAI programme in 2024. Apart from one maths project on the universal approximation theorem for MLPs all other projects are code based. The accompanying research posters for each project can be found in the BeyondAI Proceedings 2024.
For the individual research projects please navigate to the folder of each team:
- S. Amarawickrama, K. Prakash, An Elementary Proof of the Universal Approximation Theorem for Multilayer Perceptrons
- O. Igue, G. Khankhel, Weight Initialization for MLPs
- L. Vidal, J. Woodhouse, Comparing Transformers to LSTMs with Attention
- A. Singh, Y. Yifat, A Comparative Analysis of Optimizers for Classification with CNN
- P. Kundu, S. Adegbite, Non-Linear Classifiers
- M. Zaied, A. Adane, Cooperative Control of Multi-Agent Systems: An Optimal and Robust Perspective
- A. Srinivasan, S. T. Kalidoss, Graph Neural Networks for Anomaly Detection in Dynamic Graphs
- N. Saadawy, P. Raul, Linear Search vs Grover's Algorithm
- S. K. Gopal, H. Muthurengan, MNIST Digit Classification: Comparing Classical and Quantum Approaches to Hyperparameter Tuning
- E. Odiwe, Kolmogorov Arnold Networks vs Multi-Layer Perceptrons
- L. Jaafari, W. Kasthuri Arachchillage, Geometric Clifford Algebra Networks: Bridging Geometry and AI
- O. Eshmurodov, A. Ajaykumar, Overfitting vs Double Descent
- N. Haque, Early Detection of Diabetic Retinopathy Using Machine Learning
- S. Karmakar, Double Descent vs Overfitting in Deep Learning