Papers & Surveys

Multibody

This paper investigates physical diagnosis for robots facing unfamiliar conditions, defining six ordered empirical conditions required for behavior improvement, and validates the chain in controlled and public environments.

Acoustics

This paper investigates the acoustic dip phenomenon in the effective temperature of hot Brownian particles in compressible solvents, revealing how finite sound speed modifies the fluctuation-dissipation relation in the kinetic regime.

ScientificML

Proposes TASE-stabilized Time-Evolving Natural Gradient (TENG) method that projects time-discrete target states onto the neural-network manifold via local natural-gradient iterations to address stability constraints in stiff diffusion-dominated PDEs.

Multibody/Robotics

Introduces a computational framework for mechanical systems combining reservoir encoding and active inference, enabling adaptive learning in changing environments beyond traditional passive design and offline optimization constraints.

ScientificML

Proposes test-time trained flow matching for Bayesian filtering, enabling continuous distribution representation for state estimation in high-dimensional physical systems.

Materials

Presents a method using sparse differentiation to compute exact molecular Hessians from machine learning interatomic potentials, reducing computational complexity from O(N²) to O(N), overcoming limitations for large atomistic systems.

CFD

Establishes asymptotic-preserving property of exponential Euler method for stochastic reaction-diffusion-advection equations in R² under fast Hamiltonian advection with multiple critical points, reducing dynamics to a stochastic PDE on a noncompact metric graph.

ScientificML

Proposes NeSTR method that learns the S-Transform on a finite dimensional subspace of white noise test space to reconstruct stochastic solutions for Gaussian SPDEs.

Materials

Develops a general theory of rolling construction for arbitrary 2D crystals to create nanotubes, implementing an open-source library NTBuilder with desktop and web interfaces, providing a catalog of 20 million structures with exact unit cell calculations.

Multibody/Robotics

Proposes D3DWA, an adaptive DWA framework using Dueling Double Deep Q-Network to adjust weights and prediction horizon for improved robot navigation in varied environments.

ScientificML

Proposes neural network-based pulse deconvolution for FCC-ee's high-granularity dual-readout calorimeter, leveraging timing separation of Cherenkov and scintillation signals to improve energy resolution.

Multibody

DeViGrasp introduces methods to systematically examine how occlusion, segmentation-mask dropout, depth noise, and target-localization jitter affect grasp reasoning and target tracking for quadruped manipulators, improving whole-body control robustness under degraded perception.

CFD

Proposes a subcell-refined entropy-residual-driven limiter for high-order DG methods on Legendre-Gauss-Lobatto nodes, enabling robust simulation of under-resolved nonlinear hyperbolic systems while preserving accuracy via nearest-neighbor pairwise dissipation.

Materials

Neural networks trained on 4DSTEM diffraction patterns enable rapid identification of LiNiO2 and NiO material phases, providing a computationally efficient approach for analyzing large sets of materials image data.

Multibody

CHOREO enables training-free composition of heterogeneous humanoid skills learned via reinforcement learning, motion imitation, and generative modeling, bridging incompatible representations, interfaces, and controllers through unified trajectories.

CFD

An SO(3)-equivariant neural network predicts the full 6×6 grand resistance matrix for microparticles in Stokes flow, outperforming traditional scalar drag correlations by preserving orientation dependence and rotational response.

Electromagnetics

A receiver-side physics-informed residual digital twin for inter-satellite optical links that integrates Gaussian optics and quadrant-photodetector physics with an autoregressive ridge model to predict and compensate residual line-of-sight motion under sensor noise and actuator latency.

Thermal Management

This research applies Bayesian optimization and surrogate modeling to investigate urban canopy parameter ranges for heat mitigation, analyzing trade-offs among daytime air temperature, nighttime air temperature, and Universal Thermal Climate Index (UTCI) in urban environments.

Electromagnetics

This paper establishes a foundation for physically interpretable RF sensing that disentangles reflector speed from geometry, jointly recovering speed, geometry factor, relative amplitude, and width of dominant Doppler ridges for improved applicability in unconstrained real-world settings.

Multibody

A history-conditioned physics-informed flow-matching framework for probabilistic dynamics prediction of tendon-driven continuum robots, addressing uncertainties from material behavior, tendon transmission, friction, and contact.