21 citations · 24 across the 6 of their papers we have counts for
4 papers · 1 filter
Bezier Simplex Fitting: Describing Pareto Fronts of Simplicial Problems with Small Samples in Multi-objective Optimization
Ken Kobayashi, Naoki Hamada, Akiyoshi Sannai +3
Multi-objective optimization problems require simultaneously optimizing two or more objective functions. Many studies have reported that the solution set of an M-objective optimiza…
Deep Learning and Holographic QCD
Koji Hashimoto, Sotaro Sugishita, Akinori Tanaka +1
We apply the relation between deep learning (DL) and the AdS/CFT correspondence to a holographic model of QCD. Using a lattice QCD data of the chiral condensate at a finite tempera…
Self-learning Monte Carlo method with Behler-Parrinello neural networks
Yuki Nagai, Masahiko Okumura, Akinori Tanaka
We propose a general way to construct an effective Hamiltonian in the Self-learning Monte Carlo method (SLMC), which speeds up Monte Carlo simulations by training an effective mode…
Deep Learning and AdS/CFT
Koji Hashimoto, Sotaro Sugishita, Akinori Tanaka +1
We present a deep neural network representation of the AdS/CFT correspondence, and demonstrate the emergence of the bulk metric function via the learning process for given data set…