Tootfinder

Modern search demands scalable personalisation. Join Piotr Kobziakowski
at this year's Berlin Buzzwords to discover how Vespa's multi-stage ranking and tensor framework can be used for hybrid queries, multimodal retrieval, and real-time machine learning. Learn how to deploy low-latency, high-relevance search systems at petabyte scale.
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Vespa.ai’s Personalized Search: Advanced Ranking & Tensor framework
Today’s applications require search engines to unify text, vectors, and business logic with millisecond latency at petabyte scale. It’s not easy to balance speed, relevance, and personalization for a large user population and a billion scale item base. Vespa.ai, the open-source engine powering Yahoo, Perplexity, Qwant, Vinted, Spotify addresses this through multi-stage ranking with close to data tensor operations and easy to understand custom functions. Vespa’s phased architecture enables…

Talangutveckling del 2 - Specialisering och multidrottande | Podcast https://tyngre.se/podcast/tyngre-traningssnack/talangutveckling-del-2-specialisering-och-multidrottande

Talangutveckling del 2 - Specialisering och multidrottande | Podcast
Debatten om hur unga idrottare bäst utvecklas har tagit fart i Sverige de senaste åren. I detta andra avsnitt av vår serie om talangutveckling dyker vi ner i fr

On the computation of tensor functions under tensor-tensor multiplications with linear maps
Jeong-Hoon Ju, Susana Lopez-Moreno
https://arxiv.org/abs/2506.18713

On the computation of tensor functions under tensor-tensor multiplications with linear maps
In this paper we study the computation of both algebraic and non-algebraic tensor functions under the tensor-tensor multiplication with linear maps. In the case of algebraic tensor functions, we prove that the asymptotic exponent of both the tensor-tensor multiplication and the tensor polynomial evaluation problem under this multiplication is the same as that of the matrix multiplication, unless the linear map is injective. As for non-algebraic functions, we define the tensor geometric mean and…

I miss Ole Paus. This should be the national song of Norway. https://youtu.be/PX8GE4ewMbw?si=T3NxhR0TwY9ULbql

Ever wondered how Kubernetes runs on a tractor? At Berlin Buzzwords 2025, join Wieneke Keller & Sebastian Lenartowicz from Aurea Imaging to explore their innovative AgTech journey! Discover how they built an edge device with Python microservices and K3s for precision farming, tackling unique rural challenges. 
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Precision farming powered by K3s and TensorRT
Aurea Imaging is an AgTech scaleup focusing on precision farming in orchards. By retrofitting our TreeScout sensor package to their tractors, farmers are able to collect data about their orchard down to the tree level as they perform other tasks. Using onboard stereo cameras, the tractor’s high-precision GPS, a machine-vision pipeline running in real time on the device, and cloud-based analytics, this data is turned into maps used by other agricultural machines that enable the grower to utili…

Tomography for Plasma Imaging: a Unifying Framework for Bayesian Inference
D. Hamm, C. Theiler, M. Simeoni, B. P. Duval, T. Debarre, L. Simons, J. R. Queralt
https://arxiv.org/abs/2506.20232

Tomography for Plasma Imaging: a Unifying Framework for Bayesian Inference
Plasma diagnostics often employ computerized tomography to estimate emissivity profiles from a finite, and often limited, number of line-integrated measurements. Decades of algorithmic refinement have brought considerable improvements, and led to a variety of employed solutions. These often feature an underlying, common structure that is rarely acknowledged or investigated. In this paper, we present a unifying perspective on sparse-view tomographic reconstructions for plasma imaging, highlighti…

Series representation in tensor products of Banach spaces
Jochen Wengenroth
https://arxiv.org/abs/2506.21344 https://arxiv.org/pdf/25…

Series representation in tensor products of Banach spaces
We show by a ridiculously simple argument that, for any norm on the tensor product of vector spaces, every element of the completion can be represented as a convergent series of elementary tensors.

Noise-tolerant tomography of multimode linear optical interferometers with single photons
Yu. A. Biriukov, R. D. Morozov, I. V. Dyakonov, M. V. Rakhlin, A. I. Galimov, G. V. Klimko, S. V. Sorokin, I. V. Sedova, M. M. Kulagina, Yu. M. Zadiranov, A. A. Toropov, A. A. Korneev, S. P. Kulik, S. S. Straupe
https://arxiv.org/abs/2506.2…

Noise-tolerant tomography of multimode linear optical interferometers with single photons
Linear optical networks are fundamental to the advancement of quantum technologies, including quantum computing, communication, and sensing. The accurate characterization of these networks, described by unitary matrices, is crucial to their effective utilization and scalability. In this work, we present the method for reconstructing the transfer matrix of a linear optical interferometer based on the analysis of cross-correlation functions of photon counts between pairs of output modes. Our appr…

Gravitational Wave Generation and Detection in Gravitational Quantum Field Theory
Yuan-Kun Gao, Da Huang, Yue-Liang Wu
https://arxiv.org/abs/2506.21225 htt…

Gravitational Wave Generation and Detection in Gravitational Quantum Field Theory
We investigate the production and detection of gravitational waves (GWs) within the framework of Gravitational Quantum Field Theory (GQFT). In this theory, GWs exhibit five propagating modes: one scalar, two vector, and two tensor modes. Unlike General Relativity, the gravitational field equations in GQFT involve both symmetric and antisymmetric tensors, governed by their respective energy-momentum tensors, both of which can act as sources for GW radiation. By solving the linearized gravitation…

A parametric tensor ROM for the shallow water dam break problem
Md Rezwan Bin Mizan, Maxim Olshanskii, Ilya Timofeyev
https://arxiv.org/abs/2506.20007 http…

A parametric tensor ROM for the shallow water dam break problem
We develop a variant of a tensor reduced-order model (tROM) for the parameterized shallow-water dam-break problem. This hyperbolic system presents multiple challenges for model reduction, including a slow decay of the Kolmogorov $N$-width of the solution manifold, shock formation, and the loss of smooth solution dependence on parameters. These issues limit the performance of traditional Proper Orthogonal Decomposition based ROMs. Our tROM approach, based on a low-rank tensor decomposition, buil…