Novel approach for video generation using multi-marginal transport and Schrödinger bridge methods. Generates dynamic video sequences from static, unpaired image data through …
Study and implementation of Monotone Gradient Networks (MGN) for learning gradients of convex functions, optimal transport, and generative modeling on high-dimensional data.
Reimplementation of Wave-U-Net for joint speech and noise separation directly in the time domain. Developed an end-to-end 1D U-Net architecture trained from scratch for robust …
Presentation and reproduction of PersLay (Carrière et al., 2020), a neural network layer designed to process persistence diagrams. Explored graph topology embeddings, heat kernel …
Comparative study of generative and discriminative classifiers under adversarial and non-adversarial perturbations on medical imaging data. Implementation of GBZ and DBX models and …
Reimplementation and theoretical study of Gradient Boosting as functional optimization, following Biau & Cadre (Annals of Statistics, 2021). Additional experiments explored …
Graph generation challenge using a Neural Graph Generator with diffusion and variational autoencoders. Our final model, based on SAGEConv and a modified decoder, achieved the 3rd …