Khaled Kahouli
Khaled Kahouli
Doctoral Researcher
Khaled Kahouli is a PhD student in the Machine Learning Group at TU Berlin and a member of the BIFOLD graduate school. He completed his M.Sc in Computer Science at TU Berlin in 2023, specializing in generative modeling in quantum chemistry. Since 2023, his research has been centered on generative models, specifically focusing on molecule generation and structure optimization.
- Generative Models
- Machine Learning for Quantum Chemistry
- Graph Neural Networks
Khaled Kahouli, Winfried Ripken, Stefan Gugler, Oliver T Unke, Klaus-Robert Müller, Shinichi Nakajima
Disentangling total-variance and signal-to-noise-ratio improves diffusion models
Dennis Grinwald, Ankur Singha, Khaled Kahouli, Karl Jansen, Shinichi Nakajima
Data Free Training of Diffusion Models for Lattice Field Theories
Stefan Gugler, Max Eissler, Khaled Kahouli, Klaus-Robert Müller
ReactionAtlas: Ab origine exploration of chemical reaction networks with machine learning
Stefaan Simon Pierre Hessmann, Khaled Kahouli, Stefan Gugler, Michael Plainer, Frank Noé, Klaus-Robert Müller, Niklas Wolf Andreas Gebauer
Generative Pseudo-Force Fields for Molecular Generation
Khaled Kahouli, Romuald Elie, Klaus-Robert Müller, Quentin Berthet, Oliver T. Unke, Arnaud Doucet