3 papers
quant-ph2026
Geometric Prototype Learning in Quantum Hilbert Space with Matrix Product States
Kun Zhang, Lei Ding, Sheng-Chen Bai +4
Quantum probability provides a novel framework for formulating machine-learning (ML) problems in Hilbert space. We introduce a prototype-based learning scheme where class represent…
quant-ph2024
Universal scaling laws in quantum-probabilistic machine learning by tensor network towards interpreting representation and generalization powers
Sheng-Chen Bai, Shi-Ju Ran
Interpreting the representation and generalization powers has been a long-standing issue in the field of machine learning (ML) and artificial intelligence. This work contributes to…
quant-ph2024
Universal replication of chaotic characteristics by classical and quantum machine learning
Sheng-Chen Bai, Shi-Ju Ran
Replicating chaotic characteristics of non-linear dynamics by machine learning (ML) has recently drawn wide attentions. In this work, we propose that a ML model, trained to predict…