Newton-Schulz Retraction-Based Inference Enables Hidden Quantum Markov Models to Outperform Classical HMMs
Ning Ning
cs.LG, quant-ph, stat.ME
Submitted: 2026-08-06
Updated: 2026-08-10
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Unsupervised Representation Learning of DNA Sequences
- Quantum Machine Learning
- Hidden Quantum Markov Models and non-adaptive read-out of many-body states
- Robust Iterative Learning Hidden Quantum Markov Models
- Identifying DNA Sequence Motifs Using Deep Learning
- Channel-Constrained Markovian Quantum Diffusion Model from Open System Perspective
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