Tootfinder

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/5]:
- Look-Ahead Reasoning on Learning Platforms
Haiqing Zhu, Tijana Zrnic, Celestine Mendler-D\"unner
https://arxiv.org/abs/2511.14745 https://mastoxiv.page/@arXiv_csLG_bot/115575981129228810
- Deep Gaussian Process Proximal Policy Optimization
Matthijs van der Lende, Juan Cardenas-Cartagena
https://arxiv.org/abs/2511.18214 https://mastoxiv.page/@arXiv_csLG_bot/115610315210502140
- Spectral Concentration at the Edge of Stability: Information Geometry of Kernel Associative Memory
Akira Tamamori
https://arxiv.org/abs/2511.23083 https://mastoxiv.page/@arXiv_csLG_bot/115644325602130493
- xGR: Efficient Generative Recommendation Serving at Scale
Sun, Liu, Zhang, Wu, Yang, Liang, Li, Ma, Liang, Ren, Zhang, Liu, Zhang, Qian, Yang
https://arxiv.org/abs/2512.11529 https://mastoxiv.page/@arXiv_csLG_bot/115723008170311172
- Credit Risk Estimation with Non-Financial Features: Evidence from a Synthetic Istanbul Dataset
Atalay Denknalbant, Emre Sezdi, Zeki Furkan Kutlu, Polat Goktas
https://arxiv.org/abs/2512.12783 https://mastoxiv.page/@arXiv_csLG_bot/115729287232895097
- The Semantic Illusion: Certified Limits of Embedding-Based Hallucination Detection in RAG Systems
Debu Sinha
https://arxiv.org/abs/2512.15068 https://mastoxiv.page/@arXiv_csLG_bot/115740048142898391
- Towards Reproducibility in Predictive Process Mining: SPICE -- A Deep Learning Library
Stritzel, H\"uhnerbein, Rauch, Zarate, Fleischmann, Buck, Lischka, Frey
https://arxiv.org/abs/2512.16715 https://mastoxiv.page/@arXiv_csLG_bot/115745910810427061
- Differentially private Bayesian tests
Abhisek Chakraborty, Saptati Datta
https://arxiv.org/abs/2401.15502 https://mastoxiv.page/@arXiv_statML_bot/111843467510507382
- SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Reda Alami, Alexey Naumov, Eric Moulines
https://arxiv.org/abs/2402.04114
- Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
Guiomar Pescador-Barrios, Sarah Filippi, Mark van der Wilk
https://arxiv.org/abs/2408.07588 https://mastoxiv.page/@arXiv_statML_bot/112965266196097314
- Non-Perturbative Trivializing Flows for Lattice Gauge Theories
Mathis Gerdes, Pim de Haan, Roberto Bondesan, Miranda C. N. Cheng
https://arxiv.org/abs/2410.13161 https://mastoxiv.page/@arXiv_heplat_bot/113327593338897860
- Dynamic PET Image Prediction Using a Network Combining Reversible and Irreversible Modules
Sun, Zhang, Xia, Sun, Chen, Yang, Liu, Zhu, Liu
https://arxiv.org/abs/2410.22674 https://mastoxiv.page/@arXiv_eessIV_bot/113401026110345647
- Targeted Learning for Variable Importance
Xiaohan Wang, Yunzhe Zhou, Giles Hooker
https://arxiv.org/abs/2411.02221 https://mastoxiv.page/@arXiv_statML_bot/113429912435819479
- Refined Analysis of Federated Averaging and Federated Richardson-Romberg
Paul Mangold, Alain Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines
https://arxiv.org/abs/2412.01389 https://mastoxiv.page/@arXiv_statML_bot/113588027268311334
- Embedding-Driven Data Distillation for 360-Degree IQA With Residual-Aware Refinement
Abderrezzaq Sendjasni, Seif-Eddine Benkabou, Mohamed-Chaker Larabi
https://arxiv.org/abs/2412.12667 https://mastoxiv.page/@arXiv_csCV_bot/113672538318570349
- 3D Cell Oversegmentation Correction via Geo-Wasserstein Divergence
Peter Chen, Bryan Chang, Olivia A Creasey, Julie Beth Sneddon, Zev J Gartner, Yining Liu
https://arxiv.org/abs/2502.01890 https://mastoxiv.page/@arXiv_csCV_bot/113949981686723660
- DHP: Discrete Hierarchical Planning for Hierarchical Reinforcement Learning Agents
Shashank Sharma, Janina Hoffmann, Vinay Namboodiri
https://arxiv.org/abs/2502.01956 https://mastoxiv.page/@arXiv_csRO_bot/113949997485625086
- Foundation for unbiased cross-validation of spatio-temporal models for species distribution modeling
Diana Koldasbayeva, Alexey Zaytsev
https://arxiv.org/abs/2502.03480
- GraphCompNet: A Position-Aware Model for Predicting and Compensating Shape Deviations in 3D Printing
Juheon Lee (Rachel), Lei (Rachel), Chen, Juan Carlos Catana, Hui Wang, Jun Zeng
https://arxiv.org/abs/2502.09652 https://mastoxiv.page/@arXiv_csCV_bot/114017924551186136
- LookAhead Tuning: Safer Language Models via Partial Answer Previews
Liu, Wang, Luo, Yuan, Sun, Liang, Zhang, Zhou, Hooi, Deng
https://arxiv.org/abs/2503.19041 https://mastoxiv.page/@arXiv_csCL_bot/114227502448008352
- Constraint-based causal discovery with tiered background knowledge and latent variables in single...
Christine W. Bang, Vanessa Didelez
https://arxiv.org/abs/2503.21526 https://mastoxiv.page/@arXiv_statML_bot/114238919468512990
toXiv_bot_toot

It may well be that the so-called political elite surrounding Darth #Trump is currently incapable of rational thinking and is causing a lot of damage (including to US interests). But I believe that there are still strategists, particularly in the military (who are not related to Trump ;-), who will ultimately step in to put the brakes on.
Trump's EU policy is also damaging US interests enormou…

This thread is brilliant, and a call to action.
#visionzero #annarbor https://b…

Adam Goodman (@akgood.bsky.social)
The @annarborobserver.bsky.social newsletter had a decent summary of the dynamic at the #a2council Transportation Commission meeting last week (https://mailchi.mp/aaobserver/a2view-november-26-2025?e=476ffa7e6c ). But we need to take some time to talk in detail about why the city's presentation was so damaging and damning... (🧵)

Hummm.
So I was thinking about how with a couple of caster-boards and straps, the bed could be upturned and stowed in the studio. Probably? I should have figured for a fold-away really.
Still. Could work...
Then, without a bed in there, the place could turn into a dining room.
I was thinking about a shape of a table for a dinner party in there.
Oh my god.
This semi-circle table curve of wood and attachable table-legs and fold-able stools might just fit, like, under the bed normally?
Looks perfect for a card-game or a Dungeon Master setup.
Could that table and it's legs and it's chairs all fit under the bed? Probably not at it's current height. But I want to raise it a bit anyway.
🤔
Oh my god, look at this though. The projector is pointed at the wall behind the throne surrounded by the seats for the council of seven.
This could be built.
Not right away, but eventually?

this sunday, i'll be mixing collage/zones/sounds/exorcisms to accompany the great poets anne waldman & zoe brezsney alongside @… & chris dingman & pals at a special day of the dead bardo bath by psychedelic sangha at sparrow in greenpoint.

Razzia bei einem Drogendealer: Polizei läutet bei der Tür, Drogendealer macht auf.
Polizei: "Wir haben den Verdacht, dass sie mit Drogenhandel zu tun haben. Bitte schauen sie bei sich mal nach, ob sie Beweise gegen sich finden und melden sie sich bei uns."
Drogendealer bedankt sich höflich für die Information. Polizei zieht ab.
Klingt seltsam, nicht?
Warum handhaben wir das bei

🔊 #NowPlaying on #BBCRadio3:
#NewMusicShow
- Sam Amidon's Listen List
Kate Molleson with live recordings of works by Donghoon Shin and Ailis Ni Riain, plus Sam Amidon shares his latest listening.
Relisten now 👇
https://www.bbc.co.uk/programmes/m002kq69

Moments Matter: Posterior Recovery in Poisson Denoising via Log-Networks
Shirin Shoushtari, Edward P. Chandler, Ulugbek S. Kamilov
https://arxiv.org/abs/2510.07199 https://

Moments Matter: Posterior Recovery in Poisson Denoising via Log-Networks
Poisson denoising plays a central role in photon-limited imaging applications such as microscopy, astronomy, and medical imaging. It is common to train deep learning models for denoising using the mean-squared error (MSE) loss, which corresponds to computing the posterior mean $\mathbb{E}[x \mid y]$. When the noise is Gaussian, Tweedie's formula enables approximation of the posterior distribution through its higher-order moments. However, this connection no longer holds for Poisson denoising: w…