Tootfinder

sp_hypertext: Hypertext 2009 dynamic contact network
The temporal network of contacts among attendees of the ACM Hypertext 2009 conference, which spanned 2.5 days of time.
This network has 113 nodes and 2196 edges.
Tags: Social, Offline, Unweighted, Temporal
https://networks.skewed.de/net/sp_hype…

The Hybrid Code – A Hybrid Fitness & Hyrox Podcast
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/the-hybrid-code-a-hybrid-fitness-hyrox-podcast/

MARTE: EU-Staaten bauen gemeinsam Kampfpanzer mit Hybrid-Antrieb
Ein hochmoderner Kampfpanzer der EU und Norwegen soll die Kampfkraft stärken. Gemeinsam wollen die Staaten im Projekt MARTE einen solchen Panzer bauen.

Hybrid pipe dreams for the lower-upper scheme
Allen Knutson, Paul Zinn-Justin
https://arxiv.org/abs/2509.01857 https://arxiv.org/pdf/2509.01857

Hybrid pipe dreams for the lower-upper scheme
In [KU23] were introduced hybrid pipe dreams interpolating between classic and bumpless pipe dreams, each hybridization giving a different formula for double Schubert polynomials. A bijective proof was given (following [GH23]) of the independence of hybridization, but only for nonequivariant Schubert polynomials. In this paper we further generalize to hybrid generic pipe dreams, replacing the bijective proof of hybridization-independence with a Yang-Baxter-based proof that allows one to maintai…

Yesterday I released new versions of https://thi.ng/wasm-api (and its add-on packages), a modular and extensible bridge API & toolchain for hybrid JS/TS/Zig/WebAssembly apps, now updated to be compatible with the latest Zig version 0.15.1...
The update addresses some of Zig's breaking syntax & build …

Generic, modular, extensible API bridge and infrastructure for hybrid JS & WebAssembly projects

Harnessing Patterns to Support the Development of Hybrid Quantum Applications
Daniel Vietz, Martin Beisel, Johanna Barzen, Frank Leymann, Lavinia Stiliadou, Benjamin Weder
https://arxiv.org/abs/2507.00696

Harnessing Patterns to Support the Development of Hybrid Quantum Applications
Quantum computing provides computational advantages in various domains. To benefit from these advantages complex hybrid quantum applications must be built, which comprise both quantum and classical programs. Engineering these applications requires immense expertise in physics, mathematics, and software engineering. To facilitate the development of quantum applications, a corresponding quantum computing pattern language providing proven solutions to recurring problems has been presented. However…

Practical and Private Hybrid ML Inference with Fully Homomorphic Encryption
Sayan Biswas, Philippe Chartier, Akash Dhasade, Tom Jurien, David Kerriou, Anne-Marie Kerrmarec, Mohammed Lemou, Franklin Tranie, Martijn de Vos, Milos Vujasinovic
https://arxiv.org/abs/2509.01253

Practical and Private Hybrid ML Inference with Fully Homomorphic Encryption
In contemporary cloud-based services, protecting users' sensitive data and ensuring the confidentiality of the server's model are critical. Fully homomorphic encryption (FHE) enables inference directly on encrypted inputs, but its practicality is hindered by expensive bootstrapping and inefficient approximations of non-linear activations. We introduce Safhire, a hybrid inference framework that executes linear layers under encryption on the server while offloading non-linearities to the client i…

A Hybrid Input based Deep Reinforcement Learning for Lane Change Decision-Making of Autonomous Vehicle
Ziteng Gao, Jiaqi Qu, Chaoyu Chen
https://arxiv.org/abs/2509.01611 https:/…

A Hybrid Input based Deep Reinforcement Learning for Lane Change Decision-Making of Autonomous Vehicle
Lane change decision-making for autonomous vehicles is a complex but high-reward behavior. In this paper, we propose a hybrid input based deep reinforcement learning (DRL) algorithm, which realizes abstract lane change decisions and lane change actions for autonomous vehicles within traffic flow. Firstly, a surrounding vehicles trajectory prediction method is proposed to reduce the risk of future behavior of surrounding vehicles to ego vehicle, and the prediction results are input into the rein…

Observing Two-Particle Correlation Dynamics in Tunable Superconducting Bose-Hubbard Simulators
Z. T. Wang, Si-Yun Zhou, Yun-Hao Shi, Kaixuan Huang, Z. H. Yang, Jingning Zhang, Kui Zhao, Yueshan Xu, Hao Li, S. K. Zhao, Yulong Feng, Guangming Xue, Yu Liu, Wei-Guo Ma, Cai-Ping Fang, Hao-Tian Liu, Yong-Yi Wang, Kai Xu, Haifeng Yu, Heng Fan, S. P. Zhao
https://

Observing Two-Particle Correlation Dynamics in Tunable Superconducting Bose-Hubbard Simulators
The generation and propagation of quantum correlations are central to understanding many dynamical properties of quantum systems, yet their precise experimental control and characterization remain a key challenge. Here we experimentally study the two-particle correlation dynamics via quantum walks in superconducting Bose-Hubbard qutrit arrays, with tunable on-site interaction $U$ realized by Floquet engineering. Quantum walks show the characteristic change from bosonic bunching to fermionic ant…

AI-Hybrid TRNG: Kernel-Based Deep Learning for Near-Uniform Entropy Harvesting from Physical Noise
Hasan Yi\u{g}it
https://arxiv.org/abs/2507.00145 https:/…

AI-Hybrid TRNG: Kernel-Based Deep Learning for Near-Uniform Entropy Harvesting from Physical Noise
AI-Hybrid TRNG is a deep-learning framework that extracts near-uniform entropy directly from physical noise, eliminating the need for bulky quantum devices or expensive laboratory-grade RF receivers. Instead, it relies on a low-cost, thumb-sized RF front end, plus CPU-timing jitter, for training, and then emits 32-bit high-entropy streams without any quantization step. Unlike deterministic or trained artificial intelligence random number generators (RNGs), our dynamic inner-outer network coup…