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quant-ph2024★ 2 cited
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
Entanglement scaling and criticality of infinite-size quantum many-body systems in continuous space addressed by a tensor network approach
Rui Hong, Hao-Wei Cui, An-Chun Ji +1
Simulating strongly-correlated quantum systems in continuous space belongs to the most challenging and long-concerned issues in quantum physics. This work investigates the quantum…
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…