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stat.ML2024★ 4 cited
Dataset-Free Weight-Initialization on Restricted Boltzmann Machine
Muneki Yasuda, Ryosuke Maeno, Chako Takahashi
In feed-forward neural networks, dataset-free weight-initialization methods such as LeCun, Xavier (or Glorot), and He initializations have been developed. These methods randomly de…
stat.ML2022★ 6 cited
Free Energy Evaluation Using Marginalized Annealed Importance Sampling
Muneki Yasuda, Chako Takahashi
The evaluation of the free energy of a stochastic model is considered a significant issue in various fields of physics and machine learning. However, the exact free energy evaluati…
stat.ML2015★ 11 cited
Mean-Field Inference in Gaussian Restricted Boltzmann Machine
Chako Takahashi, Muneki Yasuda
A Gaussian restricted Boltzmann machine (GRBM) is a Boltzmann machine defined on a bipartite graph and is an extension of usual restricted Boltzmann machines. A GRBM consists of tw…