Check our new paper published in Scientific Reports: Greedy Gradient-free Adaptive Variational Quantum Algorithms on a Noisy Intermediate Scale Quantum Computer C. Feniou, M. Hassan, B. Claudon, A. Courtat, O....
Check this new paper published in Bioinformatics: VTX: Real-time high-performance molecular structure and dynamics visualization software. M. Maria, S. Guionnière, N. Dacquay, C. Plateau–Holleville, V. Guillaume, V. Larroque, J. Lardé,...
Check this second preprint related to the FeNNix-Bio1 foundation machine learning model: Pushing the Accuracy Limit of Foundation Neural Network Models with Quantum Monte Carlo Forces and Path Integrals ....
Check this new important preprint (ChemRXiv) introducing the FeNNix-Bio1 foundation machine learning model: A Foundation Model for Accurate Atomistic Simulations in Drug Design. T. Plé, O. Adjoua, A. Benali, E. Posenitskiy,...
Our group is interested in the development of new machine learning approaches for Computational chemistry. We focus on : algorithmic developments, ranging from machine-learning assisted parametrization of force fields and...
Check our new paper in the Journal of Physical Chemistry Letters: Lambda-ABF-OPES: Faster Convergence with High Accuracy in Alchemical Free Energy Calculations. N. Ansari, F. Jing , A. Gagelin, F....
Check our new paper in the Journal of Chemical Information and Modeling: AMOEBA Polarizable Molecular Dynamics Simulations of Guanine Quadruplexes: from the c-Kit Proto-oncogene to HIV-1. D. S. El Ahdab,...