A tailored quantum multi-programming workflow for the LUCJ ansatz enables parallel circuit execution with SQD/ext-SQD post-processing that mitigates cross-talk, yielding ethanol energies within 0.001 kcal/mol of classical HCI references.
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Felis toolkit delivers zero-shot absolute binding free energy calculations with ligand ranking performance comparable to state-of-the-art relative methods across 43 protein targets and 859 ligands.
DiffCLF reframes EBM training as supervised classification across noise levels to avoid mode blindness while remaining computationally efficient for generative models.
citing papers explorer
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A Quantum Multi-Programming Framework to Maximize Quantum Resources for the LUCJ Ansatz
A tailored quantum multi-programming workflow for the LUCJ ansatz enables parallel circuit execution with SQD/ext-SQD post-processing that mitigates cross-talk, yielding ethanol energies within 0.001 kcal/mol of classical HCI references.
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Development and large-scale benchmarks of a protein--ligand absolute binding free energy toolkit
Felis toolkit delivers zero-shot absolute binding free energy calculations with ligand ranking performance comparable to state-of-the-art relative methods across 43 protein targets and 859 ligands.
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A Diffusive Classification Loss for Learning Energy-based Generative Models
DiffCLF reframes EBM training as supervised classification across noise levels to avoid mode blindness while remaining computationally efficient for generative models.