Blog
The Cauchy–Szegö Projection for domains in $\mathbb C^n$ with minimal smoothness: weighted theory
Let $D\subset\mathbb C^n$ be a bounded, strongly pseudoconvex domain whose boundary $bD$ satisfies the minimal regularity condition of class $C^2$. A 2017 result of Lanzani \& Stein states that the Cauchy–Szeg\”{o} projection $S_\omega$ defined with respect to a bounded, positive continuous multiple...
TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation
Synthetic Electronic Health Record (EHR) time-series generation is crucial for advancing clinical machine learning models, as it helps address data scarcity by providing more training data. However, most existing approaches focus primarily on replicating statistical distributions and temporal dependencies of real-world data....
Bolt: Clothing Virtual Characters at Scale
Clothing virtual characters is a time-consuming and often manual process. Outfits can be composed of multiple garments, and each garment must be fitted to the unique shape of a character. Since characters can vary widely in size and shape, fitting outfits to...
Linear-Time Multilevel Graph Partitioning via Edge Sparsification
The current landscape of balanced graph partitioning is divided into high-quality but expensive multilevel algorithms and cheaper approaches with linear running time, such as single-level algorithms and streaming algorithms. We demonstrate how to achieve the best of both worlds with a \emph{linear...
One-dimensional $q$-state modified Potts model and its thermodynamic functions
Since its introduction, the Potts model has gained widespread popularity across various fields due to its diverse applications. Even minor advancements in this model continue to captivate scientists worldwide, and small modifications often intrigue researchers from different disciplines. This paper investigates a...
Disaggregated Deep Learning via In-Physics Computing at Radio Frequency
Modern edge devices, such as cameras, drones, and Internet-of-Things nodes, rely on deep learning to enable a wide range of intelligent applications, including object recognition, environment perception, and autonomous navigation. However, deploying deep learning models directly on the often resource-constrained edge devices...
On canonical differential equations for Calabi-Yau multi-scale Feynman integrals
We generalise a method recently introduced in the literature, that derives canonical differential equations, to multi-scale Feynman integrals with an underlying Calabi-Yau geometry. We start by recomputing a canonical form for the sunrise integral with all unequal masses. Additionally, we compute for...
On the Degree Automatability of Sum-of-Squares Proofs
The Sum-of-Squares (SoS) hierarchy, also known as Lasserre hierarchy, has emerged as a promising tool in optimization. However, it remains unclear whether fixed-degree SoS proofs can be automated [O’Donnell (2017)]. Indeed, there are examples of polynomial systems with bounded coefficients that admit...
First study of neutrino angle reconstruction using quasielastic-like interactions in MicroBooNE
We investigate the expected precision of the reconstructed neutrino direction using a {\nu}{\in}-argon quasielastic-like event topology with one muon and one proton in the final state and the reconstruction capabilities of the MicroBooNE liquid argon time projection chamber. This direction is of...
Bringing light into the Landau-Lifshitz-Gilbert equation: Consequences of its fractal non-Markovian memory kernel for optically induced magnetic inertia and magnons
The Landau-Lisfhitz-Gilbert (LLG) equation has been the cornerstone of modeling the dynamics of localized spins, viewed as classical vectors of fixed length, within nonequilibrium magnets. When light is employed as the nonequilibrium drive, the LLG equation must be supplemented with additional terms...