6 papers
NeoWorld-Pro: Programming Interactive Scenes from Monocular Images for Embodied Simulation
Yumeng He, Eachen Soong, Yichen Song +6
The advancement of Embodied AI necessitates high-quality simulation assets that faithfully mirror the real world. However, transforming raw visual observations into simulation-read…
Predicting Brain Morphogenesis via Physics-Transfer Learning
Yingjie Zhao, Yicheng Song, Fan Xu +1
Brain morphology is shaped by genetic and mechanical factors and is linked to biological development and diseases. Its fractal-like features, regional anisotropy, and complex curva…
SimMIL: A Universal Weakly Supervised Pre-Training Framework for Multi-Instance Learning in Whole Slide Pathology Images
Yicheng Song, Tiancheng Lin, Die Peng +2
Various multi-instance learning (MIL) based approaches have been developed and successfully applied to whole-slide pathological images (WSI). Existing MIL methods emphasize the imp…
Pure Exploration with Feedback Graphs
Alessio Russo, Yichen Song, Aldo Pacchiano
We study the sample complexity of pure exploration in an online learning problem with a feedback graph. This graph dictates the feedback available to the learner, covering scenario…
DimINO: Dimension-Informed Neural Operator Learning
Yichen Song, Yalun Wu, Yunbo Wang +1
In computational physics, a longstanding challenge lies in finding numerical solutions to partial differential equations (PDEs). Recently, research attention has increasingly focus…
Safe Non-Stochastic Control of Control-Affine Systems: An Online Convex Optimization Approach
Hongyu Zhou, Yichen Song, Vasileios Tzoumas
We study how to safely control nonlinear control-affine systems that are corrupted with bounded non-stochastic noise, i.e., noise that is unknown a priori and that is not necessari…