3 papers
cs.LG2026
Invariant-Measure Reasoners: Stable Representations for Latent Reasoning
Yuto Inui, Takuya Konishi, Yoshinobu Kawahara
Latent reasoning models repeatedly update a latent state using the same recurrent block. As the recurrent depth increases, the sequence of latent states may converge to a compact s…
cond-mat.dis-nn2026
Physics-inspired transformer quantum states via latent imaginary-time evolution
Kimihiro Yamazaki, Itsushi Sakata, Takuya Konishi +1
Neural quantum states (NQS) are powerful ansätze in the variational Monte Carlo framework, yet their architectures are often treated as black boxes. We propose a physically transpa…
cond-mat.str-el2025
Explorative Curriculum Learning for Strongly Correlated Electron Systems
Kimihiro Yamazaki, Takuya Konishi, Yoshinobu Kawahara
Recent advances in neural network quantum states (NQS) have enabled high-accuracy predictions for complex quantum many-body systems such as strongly correlated electron systems. Ho…