output
20132025
most citedCommon pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

1k citations

21 papers

quant-ph2025★ 1 cited

Fullqubit alchemist: Quantum algorithm for alchemical free energy calculations

Po-Wei Huang, Gregory Boyd, Gian-Luca R. Anselmetti +11

Accurately computing the free energies of biological processes is a cornerstone of computer-aided drug design, but it is a daunting task. The need to sample vast conformational spa…

cs.LG2025

Improving AI-Based Canine Heart Disease Diagnosis with Expert-Consensus Auscultation Labeling

Pinar Bisgin, Tom Strube, Niklas Tschorn +8

Noisy labels pose significant challenges for AI model training in veterinary medicine. This study examines expert assessment ambiguity in canine auscultation data, highlights the n…

quant-ph2025★ 15 cited

Faster quantum chemistry simulations on a quantum computer with improved tensor factorization and active volume compilation

Athena Caesura, Cristian L. Cortes, William Pol +8

Electronic structure calculations of molecular systems are among the most promising applications for fault-tolerant quantum computing (FTQC) in quantum chemistry and drug design. H…

quant-ph2024★ 24 cited

Reducing the runtime of fault-tolerant quantum simulations in chemistry through symmetry-compressed double factorization

Dario Rocca, Cristian L. Cortes, Jerome Gonthier +7

Quantum phase estimation based on qubitization is the state-of-the-art fault-tolerant quantum algorithm for computing ground-state energies in chemical applications. In this contex…

quant-ph2023★ 7 cited

Estimation of electrostatic interaction energies on a trapped-ion quantum computer

Pauline J. Ollitrault, Matthias Loipersberger, Robert M. Parrish +12

We present the first hardware implementation of electrostatic interaction energies using a trapped-ion quantum computer. As test system for our computation, we focus on the reducti…

quant-ph2023★ 7 cited

Improved precision scaling for simulating coupled quantum-classical dynamics

Sophia Simon, Raffaele Santagati, Matthias Degroote +3

We present a super-polynomial improvement in the precision scaling of quantum simulations for coupled classical-quantum systems in this paper. Such systems are found, for example,…