Tootfinder

Data distribution impacts the performance and generalisability of contrastive learning-based foundation models of electrocardiograms
Gul Rukh Khattak, Konstantinos Patlatzoglou, Joseph Barker, Libor Pastika, Boroumand Zeidaabadi, Ahmed El-Medany, Hesham Aggour, Yixiu Liang, Antonio H. Ribeiro, Jeffrey Annis, Antonio Luiz Pinho Ribeiro, Junbo Ge, Daniel B. Kramer, Jonathan W. Waks, Evan Brittain, Nicholas Peters, Fu Siong Ng, Arunashis Sau

Data distribution impacts the performance and generalisability of contrastive learning-based foundation models of electrocardiograms
Contrastive learning is a widely adopted self-supervised pretraining strategy, yet its dependence on cohort composition remains underexplored. We present Contrasting by Patient Augmented Electrocardiograms (CAPE) foundation model and pretrain on four cohorts (n = 5,203,352), from diverse populations across three continents (North America, South America, Asia). We systematically assess how cohort demographics, health status, and population diversity influence the downstream performance for predi…

$gg \to ZH$ : updated predictions at NLO QCD
Benjamin Campillo Aveleira, Long Chen, Joshua Davies, Giuseppe Degrassi, Pier Paolo Giardino, Ramona Gr\"ober, Gudrun Heinrich, Stephen Jones, Matthias Kerner, Johannes Schlenk, Matthias Steinhauser, Marco Vitti
https://arxiv.org/abs/2508.09905

$gg \to ZH$ : updated predictions at NLO QCD
We present state-of-the-art predictions for the inclusive cross section of gluon-initiated $ZH$ production, following the recommendations of the LHC Higgs Working Group. In particular, we include NLO QCD corrections, where the virtual corrections are obtained from the combination of a forward expansion and a high-energy expansion, and the real corrections are exact. The expanded results for the virtual corrections are compared in detail to full numerical results. The updated predictions show a …

Connecting Cores and Black Hole Dynamics Across Scales: From Globular Clusters to Massive Ellipticals
Kyle Kremer, Newlin C. Weatherford, Philip F. Hopkins, Nicholas Z. Rui, Claire S. Ye
https://arxiv.org/abs/2510.11787

Connecting Cores and Black Hole Dynamics Across Scales: From Globular Clusters to Massive Ellipticals
The centers of massive elliptical galaxies exhibit a wide range in density profiles, from central cusps to resolved cores with order kiloparsec sizes. The cored ellipticals have been linked to the presence of supermassive black hole binaries that excavate their hosts' central stellar populations through three-body encounters. This connection between cores and black holes similarly operates in globular clusters, which also exhibit a bimodality in cored and core-collapsed architectures, respectiv…

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Greg Kramer:
🎵 Heat Check
#GregKramer
https://gregkramer.bandcamp.com/track/heat-check
https://open.spotify.com/track/5dzQuBB4R9XSuobgGXhqBY

Heute vor 68 Jahren: Am 12. Oktober 1957 sammelte sich ein 9000m³ großer radioaktiver See um den #Kernreaktor #Windscale wo es zwei Tage zuvor zu einem schweren Brand kam. Die Bevölkerung wurde erst jetzt gewarnt, Millionen Liter kontaminierte Milch heimlich ins Meer entsorgt.

Der #Kormoran beeindruckt mit einer #Flügelspannweite von bis zu 1,5 Metern und seinem glänzenden, schwarzen Gefieder. Diese Meister der Fischjagd sind weltweit an Küsten und Binnengewässern zu finden. Wusstet Ihr, dass Kormorane in

Kormoran (Phalacrocorax carbo): Meister der Fischjagd und Familientiere
Der Kormorane: Von ihrer beeindruckenden Jagdtechnik unter Wasser bis hin zu den Herausforderungen, denen sie durch Populationskontrolle gegenüberstehen.

DeepWKB: Learning WKB Expansions of Invariant Distributions for Stochastic Systems
Yao Li, Yicheng Liu, Shirou Wang
https://arxiv.org/abs/2508.09529 https://

DeepWKB: Learning WKB Expansions of Invariant Distributions for Stochastic Systems
This paper introduces a novel deep learning method, called DeepWKB, for estimating the invariant distribution of randomly perturbed systems via its Wentzel-Kramers-Brillouin (WKB) approximation $u_ε(x) = Q(ε)^{-1} Z_ε(x) \exp\{-V(x)/ε\}$, where $V$ is known as the quasi-potential, $ε$ denotes the noise strength, and $Q(ε)$ is the normalization factor. By utilizing both Monte Carlo data and the partial differential equations satisfied by $V$ and $Z_ε$, the DeepWKB method computes $V$ and …

Racial bias, colorism, and overcorrection
Kenneth Colombe, Alex Krumer, Rosa Lavelle-Hill, Tim Pawlowski
https://arxiv.org/abs/2508.10585 https://arxiv.org…

Racial bias, colorism, and overcorrection
This paper examines whether increased awareness can affect racial bias and colorism. We exploit a natural experiment from the widespread publicity of Price and Wolfers (2010), which intensified scrutiny of racial bias in men's basketball officiating. We investigate refereeing decisions in the Women's National Basketball Association (WNBA), an organization with a long-standing commitment to diversity, equity, and inclusion (DEI). We apply machine learning techniques to predict player race and to…

Stability AI launches Stable Audio 2.5, which the company claims is the first audio generation model designed for "enterprise-grade use cases" (Sean Michael Kerner/Venturebeat)
https://venturebeat.com/ai/stability-ais-enterprise-au…

Clustering Deposit and Withdrawal Activity in Tornado Cash: A Cross-Chain Analysis
Raffaele Cristodaro, Benjamin Kramer, Claudio J. Tessone
https://arxiv.org/abs/2510.09433 http…

Clustering Deposit and Withdrawal Activity in Tornado Cash: A Cross-Chain Analysis
Tornado Cash is a decentralised mixer that uses cryptographic techniques to sever the on-chain trail between depositors and withdrawers. In practice, however, its anonymity can be undermined by user behaviour and operational quirks. We conduct the first cross-chain empirical study of Tornado Cash activity on Ethereum, BNB Smart Chain, and Polygon, introducing three clustering heuristics-(i) address-reuse, (ii) transactional-linkage, and (iii) a novel first-in-first-out (FIFO) temporal-matching …