arXiv:2603.28999v1 Announce Type: cross Abstract: The use of transfer learning within Bayesian optimization addresses the disadvantages of the so-called textit{cold start} problem by using source data to aid in the optimization of a target problem. We present a method that leverages an ensemble of surrogate models using transfer learning and integrates it in a constrained Bayesian optimization framework. We identify challenges particular to aircraft design optimization related to heterogeneous design variables and constraints. We propose the use of […]

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The Subscription Creep Problem Nobody Talks About I pulled my bank statements last November and counted 14 recurring subscriptions. Google One for storage. iCloud for family photos. 1Password. Three streaming services. A VPN. Backblaze for backups. Two productivity tools I barely used. Total monthly damage: $103. According to Deloitte’s 2025 Digital Media Trends report, the average U.S. streaming household pays $69/month across four video services alone, a 13% year-over-year increase. Add cloud storage, password management, and backup services, […]

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The power flow equations are non-linear multivariate equations that describe the relationship between power injections and bus voltages of electric power networks. Given a network topology, we are interested in finding network parameters with many equilibrium points. This corresponds to finding instances of the power flow equations with many real solutions. Current state-of-the art algorithms in computational algebra are not capable of answering this question for networks involving more than a small number of variables. To remedy this, […]

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arXiv:2602.00912v1 Announce Type: new Abstract: Recent initiatives advocating responsible, transparent research assessment have intensified the call to use open research information rather than proprietary databases. This study evaluates the coverage and citation representation of publications recorded in the Current Research Information Systems (CRIS), all instances of the IRIS software platform, of six Italian universities within OpenCitations, a community-owned open infrastructure. Using persistent identifiers (DOIs, PMIDs, and ISBNs) specified in the IRIS installations involved, we matched the publications recorded […]

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Table of Links Abstract and 1. Introduction Some recent trends in theoretical ML 2.1 Deep Learning via continuous-time controlled dynamical system 2.2 Probabilistic modeling and inference in DL 2.3 Deep Learning in non-Euclidean spaces 2.4 Physics Informed ML Kuramoto model 3.1 Kuramoto models from the geometric point of view 3.2 Hyperbolic geometry of Kuramoto ensembles 3.3 Kuramoto models with several globally coupled sub-ensembles Kuramoto models on higher-dimensional manifolds 4.1 Non-Abelian Kuramoto models on Lie groups 4.2 Kuramoto models […]

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Most of civilization’s electricity is generated far off-site from where it’s delivered. This is because you don’t want to be running and refueling coal/gas/nuclear plants inside cities, hydraulic/wind power can’t be moved, and solar panels are cheaper to install on flat desert terrain than on cities:  So in practice this means running power over hundreds or even thousands of kilometers. E.g. here are the Chinese long-distance lines:  Gemini 3.1 Pro-preview in AI studio American long-distance lines:  These are […]

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arXiv:2602.12023v3 Announce Type: replace-cross Abstract: Applied work under interference typically models outcomes as functions of own treatment and a low-dimensional exposure mapping of others’ treatments, even when that mapping may be misspecified. We ask what policy object such exposure-based procedures target. Taking the marginal policy effect as primitive, we show that any researcher-chosen exposure mapping induces a unique pseudo-true outcome model: the best approximation to the underlying potential outcomes within the class of functions that depend only on […]

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Brain organization is increasingly characterized through multiple imaging modalities, most notably structural connectivity (SC) and functional connectivity (FC). Integrating these inherently distinct yet complementary data sources is essential for uncovering the cross-modal patterns that drive behavioral phenotypes. However, effective integration is hindered by the high dimensionality and non-linearity of connectome data, complex non-linear SC-FC coupling, and the challenge of disentangling shared information from modality-specific variations. To address these issues, we propose the Cross-Modal Joint-Individual Variational Network (CM-JIVNet), a […]

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arXiv:2411.04551v3 Announce Type: replace-cross Abstract: Transformers are deep neural network architectures that underpin the recent successes of large language models. Unlike more classical architectures that can be viewed as point-to-point maps, a Transformer acts as a measure-to-measure map implemented as specific interacting particle system on the unit sphere: the input is the empirical measure of tokens in a prompt and its evolution is governed by the continuity equation. In fact, Transformers are not limited to empirical measures and […]

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