Tootfinder

DiffEM: Learning from Corrupted Data with Diffusion Models via Expectation Maximization
Danial Hosseintabar, Fan Chen, Giannis Daras, Antonio Torralba, Constantinos Daskalakis
https://arxiv.org/abs/2510.12691

DiffEM: Learning from Corrupted Data with Diffusion Models via Expectation Maximization
Diffusion models have emerged as powerful generative priors for high-dimensional inverse problems, yet learning them when only corrupted or noisy observations are available remains challenging. In this work, we propose a new method for training diffusion models with Expectation-Maximization (EM) from corrupted data. Our proposed method, DiffEM, utilizes conditional diffusion models to reconstruct clean data from observations in the E-step, and then uses the reconstructed data to refine the cond…

FlashVSR: Towards Real-Time Diffusion-Based Streaming Video Super-Resolution
Junhao Zhuang, Shi Guo, Xin Cai, Xiaohui Li, Yihao Liu, Chun Yuan, Tianfan Xue
https://arxiv.org/abs/2510.12747

FlashVSR: Towards Real-Time Diffusion-Based Streaming Video Super-Resolution
Diffusion models have recently advanced video restoration, but applying them to real-world video super-resolution (VSR) remains challenging due to high latency, prohibitive computation, and poor generalization to ultra-high resolutions. Our goal in this work is to make diffusion-based VSR practical by achieving efficiency, scalability, and real-time performance. To this end, we propose FlashVSR, the first diffusion-based one-step streaming framework towards real-time VSR. FlashVSR runs at appro…

The Stakeholder Engagement Division, the Infrastructure Security Division, and likely the Integrated Operations Division are believed to have been impacted.
Multiple CISA divisions targeted in shutdown layoffs, people familiar say
https://www.

Multiple CISA divisions targeted in shutdown layoffs, people familiar say
CISA units including its Stakeholder Engagement division are believed to have been hit. A DHS spokesperson said that the RIFs are meant to help get CISA “back on mission.”

Glasfaser: Von Laufzeitfallen und untergeschobenen Verträgen
Manche Glasfaser-Anbieter tricksen bei Mindestlaufzeiten oder „Beratungsprotokollen“. Wie man das durchschaut und aus dubiosen Nummern herauskommt.
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Anomalous statistics in the Langevin equation with fluctuating diffusivity: from Brownian yet non-Gaussian diffusion to anomalous diffusion and ergodicity breaking
Takuma Akimoto, Jae-Hyung Jeon, Ralf Metzler, Tomoshige Miyaguchi, Takashi Uneyama, Eiji Yamamoto
https://arxiv.org/abs/2509.12571

Anomalous statistics in the Langevin equation with fluctuating diffusivity: from Brownian yet non-Gaussian diffusion to anomalous diffusion and ergodicity breaking
Diffusive motion is a fundamental transport mechanism in physical and biological systems, governing dynamics across a wide range of scales -- from molecular transport to animal foraging. In many complex systems, however, diffusion deviates from classical Brownian behaviour, exhibiting striking phenomena such as Brownian yet non-Gaussian diffusion (BYNGD) and anomalous diffusion. BYNGD describes a frequently observed statistical feature characterised by the coexistence of linear mean-square disp…

T(R,O) Grasp: Efficient Graph Diffusion of Robot-Object Spatial Transformation for Cross-Embodiment Dexterous Grasping
Xin Fei, Zhixuan Xu, Huaicong Fang, Tianrui Zhang, Lin Shao
https://arxiv.org/abs/2510.12724

T(R,O) Grasp: Efficient Graph Diffusion of Robot-Object Spatial Transformation for Cross-Embodiment Dexterous Grasping
Dexterous grasping remains a central challenge in robotics due to the complexity of its high-dimensional state and action space. We introduce T(R,O) Grasp, a diffusion-based framework that efficiently generates accurate and diverse grasps across multiple robotic hands. At its core is the T(R,O) Graph, a unified representation that models spatial transformations between robotic hands and objects while encoding their geometric properties. A graph diffusion model, coupled with an efficient inverse…

Fully mixed virtual element schemes for steady-state poroelastic stress-assisted diffusion
Isaac Bermudez, Bryan Gomez-Vargas, Andres E. Rubiano, Ricardo Ruiz-Baier
https://arxiv.org/abs/2510.12307

Fully mixed virtual element schemes for steady-state poroelastic stress-assisted diffusion
We propose a fully mixed virtual element method for the numerical approximation of the coupling between stress-altered diffusion and linear elasticity equations with strong symmetry of total poroelastic stress (using the Hellinger--Reissner principle). A novelty of this work is that we introduce a less restrictive assumption on the stress-assisted diffusion coefficient, requiring an analysis of the perturbed diffusion equation using Banach spaces. The solvability of the continuous and discrete …

AFC anarchy: Will all 4 divisions have new champs? Appraising the Broncos, Colts, Patriots and Steelers https://www.nfl.com/news/afc-anarchy-will-all-4-divisions-have-new-champs-appraising-the-broncos-colts-patriots-and-s…

Diffusion-DFL: Decision-focused Diffusion Models for Stochastic Optimization
Zihao Zhao, Christopher Yeh, Lingkai Kong, Kai Wang
https://arxiv.org/abs/2510.11590 https://…

Diffusion-DFL: Decision-focused Diffusion Models for Stochastic Optimization
Decision-focused learning (DFL) integrates predictive modeling and optimization by training predictors to optimize the downstream decision target rather than merely minimizing prediction error. To date, existing DFL methods typically rely on deterministic point predictions, which are often insufficient to capture the intrinsic stochasticity of real-world environments. To address this challenge, we propose the first diffusion-based DFL approach, which trains a diffusion model to represent the di…

NFL playoff clinching scenarios: Which teams can secure a berth in Week 16? https://www.espn.com/nfl/story/_/id/47324099/nfl-playoff-picture-2025-clinching-scenarios-division-races-week-16