16 citations · 19 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
Intelligent diagnostic scheme for lung cancer screening with Raman spectra data by tensor network machine learning
Yu-Jia An, Sheng-Chen Bai, Lin Cheng +6
Artificial intelligence (AI) has brought tremendous impacts on biomedical sciences from academic researches to clinical applications, such as in biomarkers' detection and diagnosis…
Unsupervised Recognition of Informative Features via Tensor Network Machine Learning and Quantum Entanglement Variations
Sheng-Chen Bai, Yi-Cheng Tang, Shi-Ju Ran
Given an image of a white shoe drawn on a blackboard, how are the white pixels deemed (say by human minds) to be informative for recognizing the shoe without any labeling informati…