4 papers · 1 filter
Deterministic Decomposition of Stochastic Generative Dynamics
Xingyu Song, Yuan Mei, Naoya Takeishi
Modern generative models can be understood as probability transport from a simple base distribution to a target data distribution. Deterministic transport models offer tractable ve…
M: Reframing Training Measures for Discretized Physical Simulations
Yuan Mei, Xingyu Song, Xiaowen Song +1
Neural surrogate models for physical simulations are trained on discretized samples of continuous domains, where the induced empirical measure leads to uneven supervision, biasing…
Accurate Open-Loop Control of a Soft Continuum Robot Using Visually Learned Latent Dynamics
Henrik Krauss, Johann Licher, Naoya Takeishi +2
This work addresses open-loop control of a soft continuum robot (SCR) from video-learned latent dynamics. Visual Oscillator Networks (VONs) from previous work are used, which provi…
Sharpness-Aware Hybrid Model Learning for Architecture-Agnostic Parameter Estimation
Naoya Takeishi
Hybrid modeling, the combination of machine learning models and scientific mathematical models, enables flexible and robust data-driven prediction with partial interpretability. Ho…