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A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining, ICML'23
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.
Investigating the extent to which structural encodings in geometric methods contribute in capturing topological information and developing a generic framework (ToGePi) to inject topological and geometric information into MPNN architectures.
Repository of my BSc Artificial Intelligence thesis "3D Group Equivariant CNNs for Autism Classification".
This study aims to show that group equivariant CNNs outperform spatial transformers, on tasks which demand rotation invariance, by providing theoretical background and experimental performance comparison with detailed analysis.
My M.Sc thesis, which explores group equivariant neural networks from an algebraic perspective.
Weather prediction on stereo images using a graph equivariant convolutional neural network.
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