5 citations · 18 across the 18 of their papers we have counts for
3 papers · 1 filter
Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness
Francesco Campi, Lukas Gosch, Tom Wollschläger +2
We perform the first adversarial robustness study into Graph Neural Networks (GNNs) that are provably more powerful than traditional Message Passing Neural Networks (MPNNs). In par…
Uncertainty Estimation for Molecules: Desiderata and Methods
Tom Wollschläger, Nicholas Gao, Bertrand Charpentier +2
Graph Neural Networks (GNNs) are promising surrogates for quantum mechanical calculations as they establish unprecedented low errors on collections of molecular dynamics (MD) traje…
Efficient MILP Decomposition in Quantum Computing for ReLU Network Robustness
Nicola Franco, Tom Wollschläger, Benedikt Poggel +2
Emerging quantum computing technologies, such as Noisy Intermediate-Scale Quantum (NISQ) devices, offer potential advancements in solving mathematical optimization problems. Howeve…