Tootfinder

Is Jake Ferguson playing tonight? Why Cowboys TE is off to slow start in Week 11 https://www.sportingnews.com/us/nfl/dallas-cowboys/news/jake-ferguson-playing-tonight-why-cowboys-slow-start-week-11/02a332…

#GoodNews
https://gizmodo.com/farsighted-eye-drops-could-one-day-replace-your-reading-glasses-2000659379

Farsighted? These Eye Drops Could Eventually Replace Your Reading Glasses
New research demonstrated that special eye drops allowed patients to read extra lines on an eyesight chart for up to two years.

Jeffrey Epstein ‘threatened to destroy’ Sarah Ferguson before her apology | Jeffrey Epstein | The Guardian
https://www.theguardian.com/us-news/2025/sep/23/jeffrey-epstein-threatened-destroy-sarah-ferguson-before-her-apology

Trump Airs Frustration With Latin America as Forces Assemble (Skylar Woodhouse/Bloomberg)
https://www.bloomberg.com/news/articles/2025-11-17/trump-airs-frustration-with-latin-america-as-forces-assemble
http://www.memeorandum.com/251117/p130#a251117p130

How right-wing forces struck a coordinated blow to the BBC using a single incautious Panorama edit, after years of attacks by UK conservatives on the BBC (Jem Bartholomew/Columbia Journalism Review)
https://www.cjr.org/the_media_today/the-plan-to-bring-down-a-giant.php…

The Plan to Bring Down a Giant: How right-wing forces struck a coordinated blow to the BBC.
How right-wing forces struck a coordinated blow to the BBC.

Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting
Yifan Hu, Jie Yang, Tian Zhou, Peiyuan Liu, Yujin Tang, Rong Jin, Liang Sun
https://arxiv.org/abs/2509.14181

Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting
Representation learning techniques like contrastive learning have long been explored in time series forecasting, mirroring their success in computer vision and natural language processing. Yet recent state-of-the-art (SOTA) forecasters seldom adopt these representation approaches because they have shown little performance advantage. We challenge this view and demonstrate that explicit representation alignment can supply critical information that bridges the distributional gap between input hist…

Erinnert ihr euch an die Grenzwächter, die in der Aktion "Knobli" im Vorarlberg Schweizer EInkaufstouristen beobachteten, die Hanfsamen und Anbauzubehör kauften?
Sie zogen ihren Strafbefehl wegen Verletzung fremder Gebietshoheit weiter ans Bundesstrafgericht in Bellinzona - und wurden freigesprochen, mit Entschädigung (rechtskräftig).
SK.2024.68 Urteil vom 7. Oktober 2025

Prescott's TD dart to Ferguson boosts Cowboys' lead to 16-6 vs. Raiders https://www.nfl.com/videos/prescott-s-td-dart-to-ferguson-boosts-cowboys-lead-to-16-6-vs-raiders

From Distributional to Quantile Neural Basis Models: the case of Electricity Price Forecasting
Alessandro Brusaferri, Danial Ramin, Andrea Ballarino
https://arxiv.org/abs/2509.14113

From Distributional to Quantile Neural Basis Models: the case of Electricity Price Forecasting
While neural networks are achieving high predictive accuracy in multi-horizon probabilistic forecasting, understanding the underlying mechanisms that lead to feature-conditioned outputs remains a significant challenge for forecasters. In this work, we take a further step toward addressing this critical issue by introducing the Quantile Neural Basis Model, which incorporates the interpretability principles of Quantile Generalized Additive Models into an end-to-end neural network training framewo…

TFMAdapter: Lightweight Instance-Level Adaptation of Foundation Models for Forecasting with Covariates
Afrin Dange, Sunita Sarawagi
https://arxiv.org/abs/2509.13906 https://

TFMAdapter: Lightweight Instance-Level Adaptation of Foundation Models for Forecasting with Covariates
Time Series Foundation Models (TSFMs) have recently achieved state-of-the-art performance in univariate forecasting on new time series simply by conditioned on a brief history of past values. Their success demonstrates that large-scale pretraining across diverse domains can acquire the inductive bias to generalize from temporal patterns in a brief history. However, most TSFMs are unable to leverage covariates -- future-available exogenous variables critical for accurate forecasting in many appl…