Tootfinder

Just finished "Once For Yes" by Allie Millington. A phenomenal book dealing with tragedy, gentrification, grief, and community, it's preposterously poetic, but unfortunately has a twisted neoliberal politics lurking behind the scenes that makes me hesitate to recommend it. I enjoyed it greatly, especially the tightly choreographed prose, and the plot was both very well-paced and touching. It's fun for adults but also written for kids, which makes it all the more frustrating that despite touching on gentrification, it valorizes someone who is objectively a pretty scummy landlord, and fails to interrogate land ownership or rent in the slightest. It wouldn't be nearly the same story without the way things wrap up, but that doesn't make me comfortable with the larger messages it's sending, even if I think its messaging about grief is good, including for children.
#AmReading

GrifFinNet: A Graph-Relation Integrated Transformer for Financial Predictions
Chenlanhui Dai, Wenyan Wang, Yusi Fan, Yueying Wang, Lan Huang, Kewei Li, Fengfeng Zhou
https://arxiv.org/abs/2510.10387

GrifFinNet: A Graph-Relation Integrated Transformer for Financial Predictions
Predicting stock returns remains a central challenge in quantitative finance, transitioning from traditional statistical methods to contemporary deep learning techniques. However, many current models struggle with effectively capturing spatio-temporal dynamics and integrating multiple relational data sources. This study proposes GrifFinNet, a Graph-Relation Integrated Transformer for Financial Predictions, which combines multi-relational graph modeling with Transformer-based temporal encoding. …

Replaced article(s) found for q-fin.TR. https://arxiv.org/list/q-fin.TR/new
[1/1]:
- Efficient Triangular Arbitrage Detection via Graph Neural Networks
Di Zhang

A Hierarchical Quantized Tokenization Framework for Task-Adaptive Graph Representation Learning
Yang Xiang, Li Fan, Chenke Yin, Chengtao Ji
https://arxiv.org/abs/2510.12369 http…

A Hierarchical Quantized Tokenization Framework for Task-Adaptive Graph Representation Learning
Recent progress in language and vision foundation models demonstrates the importance of discrete token interfaces that transform complex inputs into compact sequences for large-scale modeling. Extending this paradigm to graphs requires a tokenization scheme that handles non-Euclidean structures and multi-scale dependencies efficiently. Existing approaches to graph tokenization, linearized, continuous, and quantized, remain limited in adaptability and efficiency. In particular, most current quan…

Soft Tissue Simulation and Force Estimation from Heterogeneous Structures using Equivariant Graph Neural Networks
Madina Kojanazarova, Sidady El Hadramy, Jack Wilkie, Georg Rauter, Philippe C. Cattin
https://arxiv.org/abs/2509.10125

Soft Tissue Simulation and Force Estimation from Heterogeneous Structures using Equivariant Graph Neural Networks
Accurately simulating soft tissue deformation is crucial for surgical training, pre-operative planning, and real-time haptic feedback systems. While physics-based models such as the finite element method (FEM) provide high-fidelity results, they are often computationally expensive and require extensive preprocessing. We propose a graph neural network (GNN) architecture that predicts both tissue surface deformation and applied force from sparse point clouds. The model incorporates internal anato…

Possible Quasi-Period Oscillation Signals in the Unique Event of GRB 250702DBE/EP250702a?
Fei-Fan Song, Jirong Mao
https://arxiv.org/abs/2510.10139 https://

Possible Quasi-Period Oscillation Signals in the Unique Event of GRB 250702DBE/EP250702a?
GRB 250702DBE was time-consequently triggered by GBM onboard the Fermi satellite. It is uncertain which celestial catalog is suitable for this special ultra-long event to belong to. In this paper, we comprehensively investigate the lightcurves obtained by Fermi-GBM detectors. In the energy band of 8-1000 keV, no Quasi-Period Oscillation (QPO) signals are found in the lightcurve of the first burst 250702D, a possible QPO signal of 0.046 Hz corresponding to a period of 21.7 s is found in the ligh…

Engineering Dominating Patterns: A Fine-grained Case Study
Jonathan Dransfeld, Marvin K\"unnemann, Mirza Redzic, Marcus Wunderlich
https://arxiv.org/abs/2510.12232 https://…

Engineering Dominating Patterns: A Fine-grained Case Study
The \emph{Dominating $H$-Pattern} problem generalizes the classical $k$-Dominating Set problem: for a fixed \emph{pattern} $H$ and a given graph $G$, the goal is to find an induced subgraph $S$ of $G$ such that (1) $S$ is isomorphic to $H$, and (2) $S$ forms a dominating set in $G$. Fine-grained complexity results show that on worst-case inputs, any significant improvement over the naive brute-force algorithm is unlikely, as this would refute the Strong Exponential Time Hypothesis. Nevertheless…

GraviGUT unification with revisited Pati-Salam model
Stephon Alexander, Bruno Alexandre, Michael Fine, Jo\~ao Magueijo, Ed\v{z}us N\=akums
https://arxiv.org/abs/2510.11674 https…

GraviGUT unification with revisited Pati-Salam model
We propose a graviGUT unification scheme based on the simple orthogonal group $\mathrm{SO}(1,9 ,\mathbb{C})$ that resolves the chiral duplication of weak isospin in Pati--Salam models. In the conventional $SU(4)\times SU(2)_+\times SU(2)_-$ framework, the unobserved second chiral $SU(2)$ is typically removed by ad hoc high-energy scale breaking. Here we instead \emph{geometrize} it: one $SU(2)$ factor is identified with a chiral half of the Lorentz group, so it belongs to gravity rather than to…

Novemberlektüre … Fiona Das tiefste Grab - Der Archäologie-Thriller. #büchernase #lesen

🇺🇦 Auf radioeins läuft...
Fun Lovin' Criminals:
🎵 Village Groove
#NowPlaying #FunLovinCriminals
https://funlovincriminals.bandcamp.com/track/village-groove
https://open.spotify.com/track/0Q1SGBneJn0i39CZyuH7Qq
Schon gewusst❓
Wenn Du einen Beitrag des Bots ⭐ FAVORISIERST, erfährt das nur der Bot - nicht Deine FollowerInnen.
Wenn Du einen Song weitererempfehlen möchtest, dann 🔁 TEILE ihn❗