Tootfinder

Temporal social network modeling of mobile connectivity data with graph neural networks
Joel Jaskari, Chandreyee Roy, Fumiko Ogushi, Mikko Saukkoriipi, Jaakko Sahlsten, Kimmo Kaski
https://arxiv.org/abs/2509.03319

Temporal social network modeling of mobile connectivity data with graph neural networks
Graph neural networks (GNNs) have emerged as a state-of-the-art data-driven tool for modeling connectivity data of graph-structured complex networks and integrating information of their nodes and edges in space and time. However, as of yet, the analysis of social networks using the time series of people's mobile connectivity data has not been extensively investigated. In the present study, we investigate four snapshot - based temporal GNNs in predicting the phone call and SMS activity between u…

Gbake: Baking 3D Gaussian Splats into Reflection Probes
Stephen Pasch, Joel K. Salzman, Changxi Zheng
https://arxiv.org/abs/2507.02257 https://

Gbake: Baking 3D Gaussian Splats into Reflection Probes
The growing popularity of 3D Gaussian Splatting has created the need to integrate traditional computer graphics techniques and assets in splatted environments. Since 3D Gaussian primitives encode lighting and geometry jointly as appearance, meshes are relit improperly when inserted directly in a mixture of 3D Gaussians and thus appear noticeably out of place. We introduce GBake, a specialized tool for baking reflection probes from Gaussian-splatted scenes that enables realistic reflection mappi…

Diffusion of acceptor dopants in monoclinic $\beta$-Ga$_2$O$_3$
Channyung Lee, Michael A. Scarpulla, Elif Ertekin, Joel B. Varley
https://arxiv.org/abs/2507.00906

Diffusion of acceptor dopants in monoclinic $β$-Ga$_2$O$_3$
$β$-Ga$_2$O$_3$ is a leading ultra-wide band gap semiconductor, but its performance depends on precise control over dopant incorporation and stability. In this work, we use first-principles calculations to systematically assess the diffusion behavior of eight potential deep-level substitutional acceptors (Au, Ca, Co, Cu, Fe, Mg, Mn, and Ni) in $β$-Ga$_2$O$_3$. We consider two key diffusion mechanisms: (i) interstitial diffusion under non-equilibrium conditions relevant to ion implantation, an…

Dark Forces Gathering
Peter W. Graham, Daniel Green, Joel Meyers
https://arxiv.org/abs/2508.20999 https://arxiv.org/pdf/2508.20999

Dark Forces Gathering
Recent observations of the cosmic microwave background (CMB) and baryon acoustic oscillations (BAO) show some tension with a $Λ$CDM cosmology. For one, the cosmological parameters determined by the CMB are at odds with the expansion history determined by latest BAO measurements. In addition, the combined data has placed uncomfortably strong constraints on neutrino mass. Both effects can be interpreted as negative neutrino mass, one describing the change to the expansion history and the other o…

Code Researcher: Deep Research Agent for Large Systems Code and Commit History
Ramneet Singh, Sathvik Joel, Abhav Mehrotra, Nalin Wadhwa, Ramakrishna B Bairi, Aditya Kanade, Nagarajan Natarajan
https://arxiv.org/abs/2506.11060

Code Researcher: Deep Research Agent for Large Systems Code and Commit History
Large Language Model (LLM)-based coding agents have shown promising results on coding benchmarks, but their effectiveness on systems code remains underexplored. Due to the size and complexities of systems code, making changes to a systems codebase is a daunting task, even for humans. It requires researching about many pieces of context, derived from the large codebase and its massive commit history, before making changes. Inspired by the recent progress on deep research agents, we design the fi…