Inverse reconstruction from images is a central problem in many scientific and engineering
disciplines. Recent progress on differentiable rendering has led to methods that can …

Recent works have shown that physics-inspired architectures allow the training of deep
graph neural networks (GNNs) without oversmoothing. The role of these physics is unclear …

Effective material utilization in the additive manufacturing of lightweight components is of
increasing importance. The Loo** (Load-oriented optimized paths in non-planar …

This paper develops a shape space framework for collision-aware geometric modeling,
where basic geometric operations automatically avoid inter-penetration. Shape spaces are a …

This paper presents a computational method for automatically creating fabricable 3D wire
sculptures from various input modalities, including 3D models, images, and even text. There …

Sum-of-Squares Programming (SOSP) has recently been introduced to graphics as a unified
way to address a large set of difficult problems involving higher order primitives …

In this paper, we study the statistical limits in terms of Sobolev norms of gradient descent for
solving inverse problem from randomly sampled noisy observations using a general class of …

Diagrams are essential tools for problem-solving and communication as they externalize
conceptual structures using spatial relationships. But when picking a diagramming …

Digital fabrication has revolutionized how we make physical objects with numerous
techniques to shape materials, such as additive or subtractive manufacturing, injection …

We present a method to 3D print surfaces exhibiting a prescribed varying field of anisotropic
appearance using only standard fused filament fabrication printers. This enables the …