1.1k citations · 2.6k across the 19 of their papers we have counts for
20 papers
Simulating a Post-Automation Economy
Leonard Wossnig
We develop an agent-based, stock-ow-consistent model of an economy undergoing automation, built to ask which scal instrument reaches the durable surplus that articial intelligence…
Best practices for machine learning in antibody discovery and development
Leonard Wossnig, Norbert Furtmann, Andrew Buchanan +2
Over the past 40 years, the discovery and development of therapeutic antibodies to treat disease has become common practice. However, as therapeutic antibody constructs are becomin…
The Variational Quantum Eigensolver: a review of methods and best practices
Jules Tilly, Hongxiang Chen, Shuxiang Cao +8
The variational quantum eigensolver (or VQE) uses the variational principle to compute the ground state energy of a Hamiltonian, a problem that is central to quantum chemistry and…
Quantum Machine Learning For Classical Data
Leonard Wossnig
In this dissertation, we study the intersection of quantum computing and supervised machine learning algorithms, which means that we investigate quantum algorithms for supervised m…
Statistical Limits of Supervised Quantum Learning
Carlo Ciliberto, Andrea Rocchetto, Alessandro Rudi +1
Within the framework of statistical learning theory it is possible to bound the minimum number of samples required by a learner to reach a target accuracy. We show that if the boun…
Computation of molecular excited states on IBM quantum computers using a discriminative variational quantum eigensolver
Jules Tilly, Glenn Jones, Hongxiang Chen +2
Solving for molecular excited states remains one of the key challenges of modern quantum chemistry. Traditional methods are constrained by existing computational capabilities, limi…