2 citations · 3 across the 4 of their papers we have counts for
4 papers
BERN-NN: Tight Bound Propagation For Neural Networks Using Bernstein Polynomial Interval Arithmetic
Wael Fatnassi, Haitham Khedr, Valen Yamamoto +1
In this paper, we present BERN-NN as an efficient tool to perform bound propagation of Neural Networks (NNs). Bound propagation is a critical step in wide range of NN model checker…
PolyARBerNN: A Neural Network Guided Solver and Optimizer for Bounded Polynomial Inequalities
Wael Fatnassi, Yasser shoukry
Constraints solvers play a significant role in the analysis, synthesis, and formal verification of complex embedded and cyber-physical systems. In this paper, we study the problem…
Provably Safe Model-Based Meta Reinforcement Learning: An Abstraction-Based Approach
Xiaowu Sun, Wael Fatnassi, Ulices Santa Cruz +1
While conventional reinforcement learning focuses on designing agents that can perform one task, meta-learning aims, instead, to solve the problem of designing agents that can gene…
PolyAR: A Highly Parallelizable Solver For Polynomial Inequality Constraints Using Convex Abstraction Refinement
Wael Fatnassi, Yasser Shoukry
Numerical tools for constraints solving are a cornerstone to control verification problems. This is evident by the plethora of research that uses tools like linear and convex progr…