The Machine Learning role in High Energy Physics

We explore some Standard Model (SM) extensions considering Machine Learning (ML) techniques. This is stage one, looking for recents papers, collaborations and events to build the framework and the contributions in this exciting field which combines: Physics, Computing, Mathematics and Artificial Intelligence. Our main expectations (stage two of the project) are to explore some of the new physics scenarios such as THDM, gauge extended models and vector-like models, and we investigate the observables and parameters using some ML techniques to place some bounds and define exclusion regions for the models. These techniques could prove to be useful in the understanding of flavor-changing scalar interactions, the detection of new particles and precise measurements of SM particles.