arXiv:2601.22355v1 Announce Type: new Abstract: We study the problem of quantifying how far an empirical distribution deviates from Gaussianity under the framework of optimal transport. By exploiting the cone geometry of the relative translation invariant quadratic Wasserstein space, we introduce two novel geometric quantities, the relative Wasserstein angle and the orthogonal projection distance, which provide meaningful measures of non-Gaussianity. We prove that the filling cone generated by any two rays in this space is flat, ensuring that angles, […]

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arXiv:2601.07870v1 Announce Type: new Abstract: Periodic activations such as sine preserve high-frequency information in implicit neural representations (INRs) through their oscillatory structure, but often suffer from gradient instability and limited control over multi-scale behavior. We introduce the Hyperbolic Oscillator with Saturation Control (HOSC) activation, $text{HOSC}(x) = tanhbigl(beta sin(omega_0 x)bigr)$, which exposes an explicit parameter $beta$ that controls the Lipschitz bound of the activation by $beta omega_0$. This provides a direct mechanism to tune gradient magnitudes while retaining a […]

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arXiv:2601.14417v1 Announce Type: new Abstract: Many spoken languages, including English, exhibit wide variation in dialects and accents, making accent control an important capability for flexible text-to-speech (TTS) models. Current TTS systems typically generate accented speech by conditioning on speaker embeddings associated with specific accents. While effective, this approach offers limited interpretability and controllability, as embeddings also encode traits such as timbre and emotion. In this study, we analyze the interaction between speaker embeddings and linguistically motivated phonological rules […]

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arXiv:2601.03287v1 Announce Type: new Abstract: Cybersecurity post-incident reviews are essential for identifying control failures and improving organisational resilience, yet they remain labour-intensive, time-consuming, and heavily reliant on expert judgment. This paper investigates whether Large Language Models (LLMs) can augment post-incident review workflows by autonomously analysing system evidence and identifying security policy gaps. We present a threat-informed, agentic framework that ingests log data, maps observed behaviours to the MITRE ATT&CK framework, and evaluates organisational security policies for adequacy and […]

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arXiv:2601.14335v1 Announce Type: new Abstract: This paper presents an approach for predicting the self-rated health of individuals in a future population utilising the individuals’ socio-economic characteristics. An open-source microsimulation is used to project Ireland’s population into the future where each individual is defined by a number of demographic and socio-economic characteristics. The model is disaggregated spatially at the Electoral Division level, allowing for analysis of results at that, or any broader geographical scales. Ordinal regression is utilised to […]

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arXiv:2502.20003v2 Announce Type: replace Abstract: The analytic characterization of the high-dimensional behavior of optimization for Generalized Linear Models (GLMs) with Gaussian data has been a central focus in statistics and probability in recent years. While convex cases, such as the LASSO, ridge regression, and logistic regression, have been extensively studied using a variety of techniques, the non-convex case remains far less understood despite its significance. A non-rigorous statistical physics framework has provided remarkable predictions for the behavior of […]

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How are you, hacker? 🪐 What’s happening in tech today, January 24, 2026? The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, Gold was discovered at Sutter’s Mill in 1848, NASA’s Voyager 2 spacecraft flew closely past distant Uranus in 1986, The Gonski Review was signed to reform education in Australia in 2012, and we present you with these top quality stories. From How You Can Test Your Kids Smart Toys For Privacy […]

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arXiv:2601.05293v1 Announce Type: new Abstract: Agentic AI marks an important transition from single-step generative models to systems capable of reasoning, planning, acting, and adapting over long-lasting tasks. By integrating memory, tool use, and iterative decision cycles, these systems enable continuous, autonomous workflows in real-world environments. This survey examines the implications of agentic AI for cybersecurity. On the defensive side, agentic capabilities enable continuous monitoring, autonomous incident response, adaptive threat hunting, and fraud detection at scale. Conversely, the same […]

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arXiv:2601.04286v1 Announce Type: new Abstract: Objective: Stroke is one of the leading causes of disabilities. One promising approach is to extend the rehabilitation with self-initiated robot-assisted movement therapy. To enable this, it is required to detect the patient’s intention to move to trigger the assistance of a robotic device. This intention to move can be detected from human surface electroencephalography (EEG) signals; however, it is particularly challenging to decode when classifications are performed online and asynchronously. In this […]

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Non Pneumatic tires offer a promising alternative to pneumatic tires. However, their discontinuous spoke structures present challenges in stiffness tuning, durability, and high speed vibration. This study introduces an integrated generative design and machine learning driven framework to optimize UPTIS type spoke geometries for passenger vehicles. Upper and lower spoke profiles were parameterized using high order polynomial representations, enabling the creation of approximately 250 generative designs through PCHIP based geometric variation. Machine learning models like KRR for stiffness […]

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