68 citations · 493 across the 40 of their papers we have counts for
Showing 2019Show all
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stat.ML2019★ 5 cited
Variational mean-field theory for training restricted Boltzmann machines with binary synapses
Haiping Huang
Unsupervised learning requiring only raw data is not only a fundamental function of the cerebral cortex, but also a foundation for a next generation of artificial neural networks.…
cond-mat.dis-nn2019★ 18 cited
Statistical physics of unsupervised learning with prior knowledge in neural networks
Tianqi Hou, Haiping Huang
Integrating sensory inputs with prior beliefs from past experiences in unsupervised learning is a common and fundamental characteristic of brain or artificial neural computation. H…
cond-mat.dis-nn2019★ 18 cited
Minimal model of permutation symmetry in unsupervised learning
Tianqi Hou, K. Y. Michael Wong, Haiping Huang
Permutation of any two hidden units yields invariant properties in typical deep generative neural networks. This permutation symmetry plays an important role in understanding the c…