188 citations · 275 across the 3 of their papers we have counts for
3 papers
Stochastic noise can be helpful for variational quantum algorithms
Junyu Liu, Frederik Wilde, Antonio Anna Mele +3
Saddle points constitute a crucial challenge for first-order gradient descent algorithms. In notions of classical machine learning, they are avoided for example by means of stochas…
Avoiding barren plateaus via transferability of smooth solutions in Hamiltonian Variational Ansatz
Antonio Anna Mele, Glen Bigan Mbeng, Giuseppe Ernesto Santoro +2
A large ongoing research effort focuses on Variational Quantum Algorithms (VQAs), representing leading candidates to achieve computational speed-ups on current quantum devices. The…
Exploiting symmetry in variational quantum machine learning
Johannes Jakob Meyer, Marian Mularski, Elies Gil-Fuster +4
Variational quantum machine learning is an extensively studied application of near-term quantum computers. The success of variational quantum learning models crucially depends on f…