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20232026
most citedHow quantum computing can enhance biomarker discovery

26 citations · 26 across the 9 of their papers we have counts for

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5 papers · 1 filter

quant-ph2026

Logarithmic-scale variational quantum eigensolver for off-lattice protein structure prediction in continuous torsional angle space

Fabio Cumbo, Bryan Raubenolt, Varun Puram +3

Classical and current quantum approaches to protein structure prediction (QPSP) face limitations, notably massive qubit requirements restricting near-term models to simplistic on-l…

quant-ph2026

InterQ: Communication-Aware Scheduling Across Modular QPUs with Classical and Quantum Links

Vinooth Kulkarni, Jaehyun Lee, Lauren Li +5

As quantum computing scales toward practical workloads, future systems are expected to move beyond single monolithic processors toward modular architectures that connect multiple Q…

quant-ph2026

QuMod: Parallel Quantum Job Scheduling on Modular QPUs using Circuit Cutting

Vinooth Kulkarni, Aaron Orenstein, Xinpeng Li +3

The quantum computing community is increasingly positioning quantum processors as accelerators within classical HPC workflows, analogous to GPUs and TPUs. However, many real-world…

cs.LG2026

hdlib 2.0: Extending Machine Learning Capabilities of Vector-Symbolic Architectures

Fabio Cumbo, Kabir Dhillon, Daniel Blankenberg

Following the initial publication of hdlib, a Python library for designing Vector-Symbolic Architectures (VSA), we introduce a major extension that significantly enhances its machi…

cs.SC2026

An Automatic Pipeline for the Integration of Python-Based Tools into the Galaxy Platform: Application to the anvi'o Framework

Fabio Cumbo, Jayadev Joshi, Daniel Blankenberg

The integration of command-line tools into the Galaxy platform is crucial for making complex computational methods accessible to a broader audience and ensuring reproducible resear…