Tootfinder

'Regeling van werkzaamheden' die voor de hele namiddag en avond ingepland is.
Ik heb het altijd al een best grappige omschrijving gevonden voor dit soort debatten. 😉
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A first view on the density of 5-planar graphs
Aaron B\"ungener, Jakob Franz, Michael Kaufmann, Maximilian Pfister
https://arxiv.org/abs/2505.24364 ht…

A first view on the density of 5-planar graphs
$k$-planar graphs are generalizations of planar graphs that can be drawn in the plane with at most $k > 0$ crossings per edge. One of the central research questions of $k$-planarity is the maximum edge density, i.e., the maximum number of edges a $k$-planar graph on $n$ vertices may have. While there are numerous results for the classes of general $k$-planar graphs for $k\leq 2$, there are only very few results for increasing $k=3$ or $4$ due to the complexity of the classes. We make a first st…

Approximate Light Spanners in Planar Graphs
Hung Le, Shay Solomon, Cuong Than, Csaba D. T\'oth, Tianyi Zhang
https://arxiv.org/abs/2505.24825 https://

Approximate Light Spanners in Planar Graphs
In their seminal paper, Althöfer et al. (DCG 1993) introduced the {\em greedy spanner} and showed that, for any weighted planar graph $G$, the weight of the greedy $(1+ε)$-spanner is at most $(1+\frac{2}ε) \cdot w(MST(G))$, where $w(MST(G))$ is the weight of a minimum spanning tree $MST(G)$ of $G$. This bound is optimal in an {\em existential sense}: there exist planar graphs $G$ for which any $(1+ε)$-spanner has a weight of at least $(1+\frac{2}ε) \cdot w(MST(G))$. However, as an {\em a…

Haptic Rapidly-Exploring Random Trees: A Sampling-based Planner for Quasi-static Manipulation Tasks
Lin Yang, Huu-Thiet Nguyen, Donghan Yu, Chen Lv, Domenico Campolo
https://arxiv.org/abs/2506.00351

Haptic Rapidly-Exploring Random Trees: A Sampling-based Planner for Quasi-static Manipulation Tasks
In this work, we explore how conventional motion planning algorithms can be reapplied to contact-rich manipulation tasks. Rather than focusing solely on efficiency, we investigate how manipulation aspects can be recast in terms of conventional motion-planning algorithms. Conventional motion planners, such as Rapidly-Exploring Random Trees (RRT), typically compute collision-free paths in configuration space. However, in manipulation tasks, intentional contact is often necessary. For example, whe…

On the maximum number of edges of outer k-planar graphs
Maximilian Pfister
https://arxiv.org/abs/2505.24490 https://arxiv.org/pdf/250…

On the maximum number of edges of outer k-planar graphs
We study the maximum number of straight-line segments connecting $n$ points in convex position in the plane, so that each segment intersects at most $k$ others. This question can also be framed as the maximum number of edges of an outer $k$-planar graph on $n$ vertices. We outline several approaches to tackle the problem with the best approach yielding an upper bound of $(\sqrt{2}+\varepsilon)\sqrt{k}n$ edges (with $\varepsilon \rightarrow 0$ for sufficiently large $k$). We further investigate …

Exploiting Euclidean Distance Field Properties for Fast and Safe 3D planning with a modified Lazy Theta*
Jose A. Cobano, L. Merino, F. Caballero
https://arxiv.org/abs/2505.24024

Exploiting Euclidean Distance Field Properties for Fast and Safe 3D planning with a modified Lazy Theta*
Graph search planners have been widely used for 3D path planning in the literature, and Euclidean Distance Fields (EDFs) are increasingly being used as a representation of the environment. However, to the best of our knowledge, the integration of EDFs into heuristic planning has been carried out in a loosely coupled fashion, dismissing EDF properties that can be used to accelerate/improve the planning process and enhance the safety margins of the resultant trajectories. This paper presents a fa…

Magnetic interactions as a pivotal determinant in stabilizing a novel AgIIAgIIIF5 polymorph with high spin AgIII
Daniel Jezierski, Wojciech Grochala
https://arxiv.org/abs/2506.00538

Magnetic interactions as a pivotal determinant in stabilizing a novel AgIIAgIIIF5 polymorph with high spin AgIII
Based on theoretical calculations, we introduce a new AgIIAgIIIF5 monoclinic polymorph with a rare high spin AgIII. Our analysis of the experimental xray diffraction data available in the literature reveals that this polymorph was likely prepared in the past in a mixture with the triclinic form of the same compound. Theoretical calculations reproduce very well the lattice parameters of both forms. Calculations suggest that under ambient conditions, the monoclinic form is the more energetically …

HouseTS: A Large-Scale, Multimodal Spatiotemporal U.S. Housing Dataset
Shengkun Wang, Yanshen Sun, Fanglan Chen, Linhan Wang, Naren Ramakrishnan, Chang-Tien Lu, Yinlin Chen
https://arxiv.org/abs/2506.00765

HouseTS: A Large-Scale, Multimodal Spatiotemporal U.S. Housing Dataset
Accurate house-price forecasting is essential for investors, planners, and researchers. However, reproducible benchmarks with sufficient spatiotemporal depth and contextual richness for long horizon prediction remain scarce. To address this, we introduce HouseTS a large scale, multimodal dataset covering monthly house prices from March 2012 to December 2023 across 6,000 ZIP codes in 30 major U.S. metropolitan areas. The dataset includes over 890K records, enriched with points of Interest (POI),…

Using Diffusion Ensembles to Estimate Uncertainty for End-to-End Autonomous Driving
Florian Wintel, Sigmund H. H{\o}eg, Gabriel Kiss, Frank Lindseth
https://arxiv.org/abs/2506.00560

Using Diffusion Ensembles to Estimate Uncertainty for End-to-End Autonomous Driving
End-to-end planning systems for autonomous driving are improving rapidly, especially in closed-loop simulation environments like CARLA. Many such driving systems either do not consider uncertainty as part of the plan itself, or obtain it by using specialized representations that do not generalize. In this paper, we propose EnDfuser, an end-to-end driving system that uses a diffusion model as the trajectory planner. EnDfuser effectively leverages complex perception information like fused camera …

RealDrive: Retrieval-Augmented Driving with Diffusion Models
Wenhao Ding, Sushant Veer, Yuxiao Chen, Yulong Cao, Chaowei Xiao, Marco Pavone
https://arxiv.org/abs/2505.24808

RealDrive: Retrieval-Augmented Driving with Diffusion Models
Learning-based planners generate natural human-like driving behaviors by learning to reason about nuanced interactions from data, overcoming the rigid behaviors that arise from rule-based planners. Nonetheless, data-driven approaches often struggle with rare, safety-critical scenarios and offer limited controllability over the generated trajectories. To address these challenges, we propose RealDrive, a Retrieval-Augmented Generation (RAG) framework that initializes a diffusion-based planning po…