Tootfinder

Song of the Day: Angine de Poitrine – Sherpa – the needlefish
https://theneedlefish.com/2026/04/23/song-of-the-day-angine-de-poitrine-sherpa/

Our brains—as are all brains, really—are remarkably talented at discerning patterns in all of our sensory input, filtering and interpreting it all, and letting that interpretation guide our behavior. We’re pretty good at it, really. We need to see the patterns or we die. Are we the only ones who see patterns that aren’t really there, or that make shit up to support our misinterpretations? That would explain gods, religion in general.

[Pledged: $100 of $600/month. $500 to go. Patrons: 2]
Let’s try something different: Looking for pledges to become patrons for one of our volunteers at Gaza Verified*, @…, so we can move her and her family out of living in a damp, unsafe tent and into an apartment.
Aseel’s family needs to pay $600/month rent if they’re to afford the apartment …

Never knew Patron was actually a creation of a shampoo salesman's imagination & networking.
Or that today's Patron wasn't the same as in the 90s.
▶️ The Satisfying Downfall Of Patrón
https://youtube.com/watch?v=tEdFA2jga6k&si=_1M6qEhll9kyDJvy

Mundane Things IV 🌀
普通物件 IV 🌀
📷 Nikon FE
🎞️ Ilford FP4 Plus 125, expired 1993
If you like my work, buy me a coffee from PayPal #filmphotography

T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation
Dongik Park, Hyunwoo Ryu, Suahn Bae, Keondo Park, Hyung-Sin Kim
https://arxiv.org/abs/2602.21043 https://arxiv.org/pdf/2602.21043 https://arxiv.org/html/2602.21043
arXiv:2602.21043v1 Announce Type: new
Abstract: Imputing missing values in multivariate time series remains challenging, especially under diverse missing patterns and heavy missingness. Existing methods suffer from suboptimal performance as corrupted temporal features hinder effective cross-variable information transfer, amplifying reconstruction errors. Robust imputation requires both extracting temporal patterns from sparse observations within each variable and selectively transferring information across variables--yet current approaches excel at one while compromising the other. We introduce T1 (Time series imputation with 1-to-1 channel-head binding), a CNN-Transformer hybrid architecture that achieves robust imputation through Channel-Head Binding--a mechanism creating one-to-one correspondence between CNN channels and attention heads. This design enables selective information transfer: when missingness corrupts certain temporal patterns, their corresponding attention pathways adaptively down-weight based on remaining observable patterns while preserving reliable cross-variable connections through unaffected channels. Experiments on 11 benchmark datasets demonstrate that T1 achieves state-of-the-art performance, reducing MSE by 46% on average compared to the second-best baseline, with particularly strong gains under extreme sparsity (70% missing ratio). The model generalizes to unseen missing patterns without retraining and uses a consistent hyperparameter configuration across all datasets. The code is available at https://github.com/Oppenheimerdinger/T1.
toXiv_bot_toot

Playing with improvising some sanquhar-style patterns in the round (so I don't have to do purls), and decided to turn it into a sock for my lovely Zoom L6 portable mixer. #knitting

La patronne d’Engie dénonce les idées « mauvaises pour la France » du RN en matière d’énergie
https://www.lemonde.fr/politique/article/2026/04/22/la-patronne-d…

La patronne d’Engie dénonce les idées « mauvaises pour la France » du RN en matière d’énergie
Catherine MacGregor affirme avoir notamment défendu la transition énergétique auprès de Marine Le Pen, critiquant les mesures mises en avant par son parti au moment de la dissolution de l’Assemblée nationale en 2024.

RE: https://mastodon.ar.al/@aral/116130113129035572
We have a fourth patron – thank you @… with a €50/month pledge – and our …

RE: https://mastodon.social/@EndIsraeliApartheid/116458442461704301
Almost as if there’s a pattern here or something: liars lie, murderers murder, thieves stealing people’s land and homes steal people’s land and homes, monsters committing genoc…