activity
20232025
most citedKAN 2.0: Kolmogorov-Arnold Networks Meet Science

49 citations · 65 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CE2025

Newton to Einstein: Axiom-Based Discovery via Game Design

Pingchuan Ma, Benjamin Tod Jones, Tsun-Hsuan Wang +4

This position paper argues that machine learning for scientific discovery should shift from inductive pattern recognition to axiom-based reasoning. We propose a game design framewo…

cs.RO2025★ 1 cited

Fabrica: Dual-Arm Assembly of General Multi-Part Objects via Integrated Planning and Learning

Yunsheng Tian, Joshua Jacob, Yijiang Huang +10

Multi-part assembly poses significant challenges for robots to execute long-horizon, contact-rich manipulation with generalization across complex geometries. We present Fabrica, a…

cs.RO2025

AI-Enhanced Automatic Design of Efficient Underwater Gliders

Peter Yichen Chen, Pingchuan Ma, Niklas Hagemann +4

The development of novel autonomous underwater gliders has been hindered by limited shape diversity, primarily due to the reliance on traditional design tools that depend heavily o…

cs.CV2025

TopoGaussian: Inferring Internal Topology Structures from Visual Clues

Xiaoyu Xiong, Changyu Hu, Chunru Lin +3

We present TopoGaussian, a holistic, particle-based pipeline for inferring the interior structure of an opaque object from easily accessible photos and videos as input. Traditional…

cs.RO2024★ 1 cited

Learning Object Properties Using Robot Proprioception via Differentiable Robot-Object Interaction

Peter Yichen Chen, Chao Liu, Pingchuan Ma +5

Differentiable simulation has become a powerful tool for system identification. While prior work has focused on identifying robot properties using robot-specific data or object pro…

cs.LG2024★ 49 cited

KAN 2.0: Kolmogorov-Arnold Networks Meet Science

Ziming Liu, Pingchuan Ma, Yixuan Wang +2

A major challenge of AI + Science lies in their inherent incompatibility: today's AI is primarily based on connectionism, while science depends on symbolism. To bridge the two worl…

cs.LG2024★ 9 cited

LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery

Pingchuan Ma, Tsun-Hsuan Wang, Minghao Guo +5

Large Language Models have recently gained significant attention in scientific discovery for their extensive knowledge and advanced reasoning capabilities. However, they encounter…

cs.CV2024★ 1 cited

Physically Compatible 3D Object Modeling from a Single Image

Minghao Guo, Bohan Wang, Pingchuan Ma +6

We present a computational framework that transforms single images into 3D physical objects. The visual geometry of a physical object in an image is determined by three orthogonal…

physics.flu-dyn2024

NeuralFluid: Neural Fluidic System Design and Control with Differentiable Simulation

Yifei Li, Yuchen Sun, Pingchuan Ma +4

We present a novel framework to explore neural control and design of complex fluidic systems with dynamic solid boundaries. Our system features a fast differentiable Navier-Stokes…

cs.RO2023★ 4 cited

DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models

Tsun-Hsuan Wang, Juntian Zheng, Pingchuan Ma +6

Nature evolves creatures with a high complexity of morphological and behavioral intelligence, meanwhile computational methods lag in approaching that diversity and efficacy. Co-opt…