most citedBERN-NN: Tight Bound Propagation For Neural Networks Using Bernstein Polynomial Interval Arithmetic

2 citations · 2 across the 3 of their papers we have counts for

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3 papers

cs.LG2022★ 2 cited

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…

cs.LG2021

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…

math.OC2021

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…