I’m currently a PhD student in Machine Learning in Colorado Boulder University. I’ve graduated from Ecole Polytechnique with a degree in Computational Mathematics with a minor in Machine Learning and hold a master in “Mathematics, Computer Vision, and Learning” from ENS Paris-Saclay (aka ENS Cachan).
My interests mainly lie within applied artificial intelligence and machine learning; I worked on deep and hierarchical reinforcement learning as an intern in RIKEN AIP Labs, Tokyo. Currently, I’m exploring more ML techniques, especially Unsupervised Learning methods as part of my PhD, supervied by Claire Monteleoni.
- Reinfocement Learning with Options
- Policy Gradient Methods
- Deep Automatic Chord Recognition
- Artistic Styles : Neural Style Transfer vs Generative Adversarial Networks
- A Martingale Hypothesis Test
- Volatility Derivatives : Variance Swap
- Spectral Clustering for Online Face Recognition
- Supervised Learning, MVA [Matlab Code]
- Mixture of Probabilistic PCA
- SymSpell implementation, Lavenshtein Edit Distance
- Used for tweets normalisation, NLP, MVA [Code]
- Ant Colony Algorithm