5 citations · 11 across the 10 of their papers we have counts for
12 papers
Pareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models
Koki Takeshita, Kenji Uebayashi, Hikaru Tomonari +6
Recent studies have proposed reinforcement learning with verifiable rewards (RLVR) methods that enable LLMs to generate high-quality RTL circuits from natural-language specificatio…
Learning Unknown Constraints without Unsafe Data via Optimality and Counterfactual Regularization
Zhouyu Zhang, Chih-Yuan Chiu, Glen Chou
Learning from demonstrations (LfD) provides a framework for inferring unknown constraints from locally optimal, constraint-satisfying expert behavior. Existing approaches largely f…
Bridging the Sim-to-Real Gap in Semiconductor Visual Program Synthesis via Input Binarization
Yusuke Ohtsubo, Kota Dohi, Koichiro Yawata +2
Precise parametric control over circuit geometry is essential for semiconductor inspection, yet obtaining sufficient real training data remains costly. Although generative models s…
Data-driven oscillator model for turbulent flows with multiple dominant frequencies
Youngjae Kim, Koichiro Yawata, Hiroya Nakao +1
The complex dynamics of high-dimensional oscillatory flows can be simplified using phase-reduction analysis, providing a deeper understanding of the flow response to external pertu…
Hypergraph Neural Networks Accelerate MUS Enumeration
Hiroya Ijima, Koichiro Yawata
Enumerating Minimal Unsatisfiable Subsets (MUSes) is a fundamental task in constraint satisfaction problems (CSPs). Its major challenge is the exponential growth of the search spac…
LaSTR: Language-Driven Time-Series Segment Retrieval
Kota Dohi, Harsh Purohit, Tomoya Nishida +6
Effectively searching time-series data is essential for system analysis, but existing methods often require expert-designed similarity criteria or rely on global, series-level desc…
Global Phase Synchronization Decoupled from Amplitude Dynamics
Koichiro Yawata, Hiroya Nakao
The Kuramoto model is a canonical framework for analyzing phase synchronization, yet its utility is restricted to the vicinity of the oscillator's unperturbed limit cycle. Here, we…
Data-driven phase control for limit-cycle oscillators under partial observation
Koichiro Yawata, Norihisa Namura, Yuzuru Kato +1
Controlling rhythmic systems, typically modeled as limit-cycle oscillators, is an important subject in real-world problems. Phase reduction theory, which simplifies the multidimens…
Phase autoencoder for rapid data-driven synchronization of rhythmic spatiotemporal patterns
Koichiro Yawata, Ryo Sakuma, Kai Fukami +2
We present a machine-learning method for data-driven synchronization of rhythmic spatiotemporal patterns in reaction-diffusion systems. Based on the phase autoencoder [Yawata {\it…
Phase autoencoder for limit-cycle oscillators
Koichiro Yawata, Kai Fukami, Kunihiko Taira +1
We present a phase autoencoder that encodes the asymptotic phase of a limit-cycle oscillator, a fundamental quantity characterizing its synchronization dynamics. This autoencoder i…
QUBO-inspired Molecular Fingerprint for Chemical Property Prediction
Koichiro Yawata, Yoshihiro Osakabe, Takuya Okuyama +1
Molecular fingerprints are widely used for predicting chemical properties, and selecting appropriate fingerprints is important. We generate new fingerprints based on the assumption…
QUBO Decision Tree: Annealing Machine Extends Decision Tree Splitting
Koichiro Yawata, Yoshihiro Osakabe, Takuya Okuyama +1
This paper proposes an extension of regression trees by quadratic unconstrained binary optimization (QUBO). Regression trees are very popular prediction models that are trainable w…