9 citations · 15 across the 7 of their papers we have counts for
7 papers
Bayesian Symbolic Regression with Entropic Reinforcement Learning
Oussama Boussif, Mohammed Mahfoud, Younesse Kaddar +6
Symbolic regression is the problem of finding an algebraic expression describing a stochastic dependence of a target variable on a set of inputs. Unlike forms of regression that fi…
Scalable and Cost-Efficient de Novo Template-Based Molecular Generation
Piotr Gaiński, Oussama Boussif, Andrei Rekesh +5
Template-based molecular generation offers a promising avenue for drug design by ensuring generated compounds are synthetically accessible through predefined reaction templates and…
Action abstractions for amortized sampling
Oussama Boussif, Léna Néhale Ezzine, Joseph D Viviano +6
As trajectories sampled by policies used by reinforcement learning (RL) and generative flow networks (GFlowNets) grow longer, credit assignment and exploration become more challeng…
Improving day-ahead Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context
Oussama Boussif, Ghait Boukachab, Dan Assouline +4
Solar power harbors immense potential in mitigating climate change by substantially reducing CO emissions. Nonetheless, the inherent variability of solar irradiance poses a s…
MAgNet: Mesh Agnostic Neural PDE Solver
Oussama Boussif, Dan Assouline, Loubna Benabbou +1
The computational complexity of classical numerical methods for solving Partial Differential Equations (PDE) scales significantly as the resolution increases. As an important examp…
Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning
Dianbo Liu, Vedant Shah, Oussama Boussif +6
In cooperative multi-agent reinforcement learning, a team of agents works together to achieve a common goal. Different environments or tasks may require varying degrees of coordina…
Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel
Dianbo Liu, Vedant Shah, Oussama Boussif +6
In Multi-Agent Reinforcement Learning (MARL), specialized channels are often introduced that allow agents to communicate directly with one another. In this paper, we propose an alt…