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Julien Roy

royjulie@mila.quebec
Doctorat - Polytechnique Montréal
Superviseur⋅e principal⋅e
Chris Pal
Co-superviseur⋅e
Pierre-Luc Bacon
Github
Google Scholar

Publications

Goal-conditioned GFlowNets for Controllable Multi-Objective Molecular Design
Julien Roy
Pierre-Luc Bacon
Chris Pal
Emmanuel Bengio
In recent years, in-silico molecular design has received much attention from the machine learning community. When designing a new compound f… (voir plus)or pharmaceutical applications, there are usually multiple properties of such molecules that need to be optimised: binding energy to the target, synthesizability, toxicity, EC50, and so on. While previous approaches have employed a scalarization scheme to turn the multi-objective problem into a preference-conditioned single objective, it has been established that this kind of reduction may produce solutions that tend to slide towards the extreme points of the objective space when presented with a problem that exhibits a concave Pareto front. In this work we experiment with an alternative formulation of goal-conditioned molecular generation to obtain a more controllable conditional model that can uniformly explore solutions along the entire Pareto front.
2023-06-23
ICML.cc/2023/Workshop/DeployableGenerativeAI (publié)
doi.org
openreview.net