Tootfinder

#running slow is hard but my fitness is such that it requires a rebuild of the foundation. Trying to stay in HR2 means a decent amount of walking interspersed. I don’t love it, but it’s necessary.
I have a much more open schedule now, so I should be able to get out and run regularly. The trick will be staying patient and trusting the process.

We in Game Workers Unite Ireland stand in solidarity with Animation Workers of Ireland, and the international trade union coalition happening to organise against the threat of AI in the animation industry, and we support their call to acton.
Join them Thursday 12 June at 14:00 at the Pâquier in Annecy!!
#Animation

A Disentangled Representation Learning Framework for Low-altitude Network Coverage Prediction
Xiaojie Li, Zhijie Cai, Nan Qi, Chao Dong, Guangxu Zhu, Haixia Ma, Qihui Wu, Shi Jin
https://arxiv.org/abs/2507.14186

A Disentangled Representation Learning Framework for Low-altitude Network Coverage Prediction
The expansion of the low-altitude economy has underscored the significance of Low-Altitude Network Coverage (LANC) prediction for designing aerial corridors. While accurate LANC forecasting hinges on the antenna beam patterns of Base Stations (BSs), these patterns are typically proprietary and not readily accessible. Operational parameters of BSs, which inherently contain beam information, offer an opportunity for data-driven low-altitude coverage prediction. However, collecting extensive low-a…

Exploiting Policy Idling for Dexterous Manipulation
Annie S. Chen, Philemon Brakel, Antonia Bronars, Annie Xie, Sandy Huang, Oliver Groth, Maria Bauza, Markus Wulfmeier, Nicolas Heess, Dushyant Rao
https://arxiv.org/abs/2508.15669

Exploiting Policy Idling for Dexterous Manipulation
Learning-based methods for dexterous manipulation have made notable progress in recent years. However, learned policies often still lack reliability and exhibit limited robustness to important factors of variation. One failure pattern that can be observed across many settings is that policies idle, i.e. they cease to move beyond a small region of states when they reach certain states. This policy idling is often a reflection of the training data. For instance, it can occur when the data contain…

INLA-RF: A Hybrid Modeling Strategy for Spatio-Temporal Environmental Data
Mario Figueira, Michela Cameletti, Luca Patelli
https://arxiv.org/abs/2507.18488 https://

INLA-RF: A Hybrid Modeling Strategy for Spatio-Temporal Environmental Data
Environmental processes often exhibit complex, non-linear patterns and discontinuities across space and time, posing significant challenges for traditional geostatistical modeling approaches. In this paper, we propose a hybrid spatio-temporal modeling framework that combines the interpretability and uncertainty quantification of Bayesian models -- estimated using the INLA-SPDE approach -- with the predictive power and flexibility of Random Forest (RF). Specifically, we introduce two novel algor…

Noise-Induced Collective Memory in Schooling Fish
Alyssa Chan, Eva Kanso
https://arxiv.org/abs/2507.16102 https://arxiv.org/pdf/2507.…

Noise-Induced Collective Memory in Schooling Fish
Schooling fish often self-organize into a variety of collective patterns, from polarized schooling to rotational milling. Mathematical models support the emergence of these large-scale patterns from local decentralized interactions, in the absence of individual memory and group leadership. In a popular model where individual fish interact locally following rules of avoidance, alignment, and attraction, the group exhibits collective memory: changes in individual behavior lead to emergent pattern…

Fine-tuning ORBGRAND with Very Few Channel Soft Values
Li Wan, Huarui Yin, Wenyi Zhang
https://arxiv.org/abs/2507.08696 https://arxiv…

Fine-tuning ORBGRAND with Very Few Channel Soft Values
Guessing random additive noise decoding (GRAND) is a universal decoding paradigm that decodes by repeatedly testing error patterns until identifying a codeword, where the ordering of tests is generated by the received channel values. On one hand, while testing error patterns in a descending order of posterior probabilities leads to maximum likelihood decoding, its implementation complexity is prohibitive. On the other hand, testing error patterns with a prescribed set of error patterns permuted…

A non-face characterization of spheres on few vertices
Shuai Huang, Jasper Miller, Daniel Rose-Levine, Steven Simon
https://arxiv.org/abs/2507.06120 https:…

A non-face characterization of spheres on few vertices
We give a relatively simple characterization of simplicial $d$-spheres on $d+4$ vertices; our criteria are in terms of the intersection patterns of a simplicial complex's minimal non-faces. Namely, let $Σ$ be a simplicial complex with vertex set $[d+4]$ and let $\mathcal{F}=\{A_0,\ldots, A_{n-1}\}$ be its family of minimal non-faces, indices taken in $\mathbb{Z}_n$. Then $Σ$ is a $d$-sphere if and only if the following hold: $n\geq 3$ is odd, successive $A_i$ are disjoint, and the alternating…

KMT-2024-BLG-0404L: A triple microlensing system consisting of a star, a brown dwarf, and a planet
Cheongho Han, Andrzej Udalski, Chung-Uk Lee, Yoon-Hyun Ryu, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Kyu-Ha Hwang, Youn Kil Jung, In-Gu Shin, Yossi Shvartzvald, Jennifer C. Yee, Hongjing Yang, Weicheng Zang, Doeon Kim, Dong-Jin Kim, Byeong-Gon Park, Richard W. Pogge, Przemek Mr\'oz, Micha{\l} K. Szyma\'nski, Jan Skowron, Rados{\l}aw Poleski, Igor Soszy\'nski, Pawe{\l} Pi…

KMT-2024-BLG-0404L: A triple microlensing system consisting of a star, a brown dwarf, and a planet
We have investigated the lensing event KMT-2024-BLG-0404. The light curve of the event exhibited a complex structure with multiple distinct features, including two prominent caustic spikes, two cusp bumps, and a brief discontinuous feature between the caustic spikes. While a binary-lens model captured the general anomaly pattern, it could not account for a discontinuous anomaly feature between the two caustic spikes. To explore the origin of the unexplained feature, we conducted more advanced m…

Nonparametric inference for nonstationary spatial point processes
Izabel Nolau, Fl\'avio B. Gon\c{c}alves, Dani Gamerman
https://arxiv.org/abs/2507.17600 https://

Nonparametric inference for nonstationary spatial point processes
Point pattern data often exhibit features such as abrupt changes, hotspots and spatially varying dependence in local intensity. Under a Poisson process framework, these correspond to discontinuities and nonstationarity in the underlying intensity function -- features that are difficult to capture with standard modeling approaches. This paper proposes a spatial Cox process model in which nonstationarity is induced through a random partition of the spatial domain, with conditionally independent G…