49 citations · 117 across the 12 of their papers we have counts for
7 papers
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…
Lite2Relight: 3D-aware Single Image Portrait Relighting
Pramod Rao, Gereon Fox, Abhimitra Meka +8
Achieving photorealistic 3D view synthesis and relighting of human portraits is pivotal for advancing AR/VR applications. Existing methodologies in portrait relighting demonstrate…
A Universal Scaling Law for Intrinsic Fracture Energy of Networks
Chase Hartquist, Shu Wang, Qiaodong Cui +3
Networks of interconnected materials permeate throughout nature, biology, and technology due to exceptional mechanical performance. Despite the importance of failure resistance in…
Neural Stress Fields for Reduced-order Elastoplasticity and Fracture
Zeshun Zong, Xuan Li, Minchen Li +6
We propose a hybrid neural network and physics framework for reduced-order modeling of elastoplasticity and fracture. State-of-the-art scientific computing models like the Material…
Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction
Minghao Guo, Veronika Thost, Samuel W Song +4
The prediction of molecular properties is a crucial task in the field of material and drug discovery. The potential benefits of using deep learning techniques are reflected in the…
How Can Large Language Models Help Humans in Design and Manufacturing?
Liane Makatura, Michael Foshey, Bohan Wang +15
The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design. We investigate the application of this tool across the…