Tootfinder

Überfüllter Traumstrand, zu gereizte Gendern-Debatte, die ewige Suche nach unabhängigen sozialen Medien und digitaler Souveränität und ChatGPT als Fußball-Experte. Alles Themen dieser Wochenschau.
http://stefanpfeiffer.blog/2025/07/11/…

Gereizte #Wochenschau zwischen Elafonisi, Gendern und dem Fediverse
Überfüllter Traumstrand, zu gereizte Gendern-Debatte, die ewige Suche nach unabhängigen sozialen Medien und digitaler Souveränität und ChatGPT als Fußball-Experte. Alles Themen dieser Wochenschau.…

Newsflash: no data substantiating the assertion that 'discrimination has been sufficiently addressed' makes this arbitrary and capricious and unlawful.
USDA Ends Consideration of Race and Gender for Grants and Loans | Civil Eats
https://civileats.com/2025/07/10/usda-ends-consideration-of-race-and-gender-for-grants-and-loans/

Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling
Haoyu Wu, Diankun Wu, Tianyu He, Junliang Guo, Yang Ye, Yueqi Duan, Jiang Bian
https://arxiv.org/abs/2507.07982

Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling
Videos inherently represent 2D projections of a dynamic 3D world. However, our analysis suggests that video diffusion models trained solely on raw video data often fail to capture meaningful geometric-aware structure in their learned representations. To bridge this gap between video diffusion models and the underlying 3D nature of the physical world, we propose Geometry Forcing, a simple yet effective method that encourages video diffusion models to internalize latent 3D representations. Our ke…

Geometric flow regularization in latent spaces for smooth dynamics with the efficient variations of curvature
Andrew Gracyk
https://arxiv.org/abs/2506.09679

Geometric flow regularization in latent spaces for smooth dynamics with the efficient variations of curvature
We design strategies in nonlinear geometric analysis to temper the effects of adversarial learning for sufficiently smooth data of numerical method-type dynamics in encoder-decoder methods, variational and deterministic, through the use of geometric flow regularization. We augment latent spaces with geometric flows to control structure. Our techniques rely on adaptations of curvature and Ricci flow. We invent new geometric flows or discover them neurally and non-parametrically. All of our flows…

The $\mathcal{D}$-Geometric Hilbert Scheme -- Part I: Involutivity and Stability
Jacob Kryczka, Artan Sheshmani
https://arxiv.org/abs/2507.07937 https://…

The $\mathcal{D}$-Geometric Hilbert Scheme -- Part I: Involutivity and Stability
We construct a moduli space of formally integrable and involutive ideal sheaves arising from systems of partial differential equations (PDEs) in the algebro-geometric setting, by introducing the $\mathcal{D}$-Hilbert and $\mathcal{D}$-Quot functors in the sense of Grothendieck and establishing their representability. Central to this construction is the notion of Spencer (semi-)stability, which presents an extension of classical stability conditions from gauge theory and complex geometry, and wh…

Extended Spherical Geometry Algorithm for Spaceborne SAR Processing in Stripmap and TOPS Imaging Modes
Xinhua Mao, Manyi Tao, Jixia Fan
https://arxiv.org/abs/2506.08620

Extended Spherical Geometry Algorithm for Spaceborne SAR Processing in Stripmap and TOPS Imaging Modes
The Spherical Geometry Algorithm (SGA) demonstrates superior capability in achieving efficient and precise spaceborne SAR image formation processing, even under challenging imaging conditions including non-linear radar trajectories and spherical Earth surface geometry. Nevertheless, the original SGA is specifically developed for spotlight SAR data processing and can't directly applied to processing spaceborne SAR data in other modes. In this paper, we first analyze the limitations of the SGA al…

Sensor Fusion for Track Geometry Monitoring: Integrating On-Board Data and Degradation Models via Kalman Filtering
Huy Truong-Ba, Jacky Chin, Michael E. Cholette, Pietro Borghesani
https://arxiv.org/abs/2506.08028

Sensor Fusion for Track Geometry Monitoring: Integrating On-Board Data and Degradation Models via Kalman Filtering
Track geometry monitoring is essential for maintaining the safety and efficiency of railway operations. While Track Recording Cars (TRCs) provide accurate measurements of track geometry indicators, their limited availability and high operational costs restrict frequent monitoring across large rail networks. Recent advancements in on-board sensor systems installed on in-service trains offer a cost-effective alternative by enabling high-frequency, albeit less accurate, data collection. This study…

So, they don’t have anything against *that* type of gender-affirming care https://www.economist.com/united-states/2025/07/08/american-men-are-hungry-for-injectable-testosterone

Nach Vandalismus: Waymo beschränkt Fahrdienste in Los Angeles und San Francisco
Autonome Taxis von Waymo sind in San Francisco und Los Angeles ein gewohnter Anblick. Nachdem einige angezündet wurden, fährt die Firma das Angebot herunter.

sparseGeoHOPCA: A Geometric Solution to Sparse Higher-Order PCA Without Covariance Estimation
Renjie Xu, Chong Wu, Maolin Che, Zhuoheng Ran, Yimin Wei, Hong Yan
https://arxiv.org/abs/2506.08670

sparseGeoHOPCA: A Geometric Solution to Sparse Higher-Order PCA Without Covariance Estimation
We propose sparseGeoHOPCA, a novel framework for sparse higher-order principal component analysis (SHOPCA) that introduces a geometric perspective to high-dimensional tensor decomposition. By unfolding the input tensor along each mode and reformulating the resulting subproblems as structured binary linear optimization problems, our method transforms the original nonconvex sparse objective into a tractable geometric form. This eliminates the need for explicit covariance estimation and iterative …