Knowledge catalogue
arXiv:2603.23318v2 Announce Type: replace Abstract: Among the different possible strategies for evaluating the reliability of individual predictions of classifiers, robustness quantification stands ou
arXiv:2607.08370v1 Announce Type: cross Abstract: We derive bounds for the volume of tubular neighbourhoods of smooth Pfaffian hypersurfaces, generalising known results for algebraic varieties. The bo
arXiv:2607.06269v1 Announce Type: new Abstract: Current large language models (LLMs) are fundamentally stateless: their behavior is fully determined by input at inference time, and any higher-order co
arXiv:2607.06306v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated growing competence in web page generation. However, existing text-driven approaches rely on complex pro
arXiv:2607.06383v1 Announce Type: new Abstract: Wheelchair users call for assistive mobility systems that provide active support, adapt to dynamic environments, and are intuitive and user-friendly. Ho
arXiv:2606.31639v1 Announce Type: cross Abstract: Large language models are no longer only text generators. They are increasingly embedded in retrieval pipelines, enterprise assistants, coding environ
arXiv:2601.23225v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (RL) is increasingly deployed in resource-constrained environments, yet go-to function approximators - multilayer
arXiv:2606.28519v1 Announce Type: new Abstract: Training operator-learning models for large-scale problems governed by partial differential equations (PDEs) is challenging due to the curse of dimensio
arXiv:2309.05055v2 Announce Type: replace Abstract: The motions of mechanisms can be described in terms of screw coordinates by means of an exponential mapping. The product of exponentials (POE) descr
arXiv:2606.29664v1 Announce Type: new Abstract: Geospatial foundation models pretrained on satellite imagery promise broad generalization across remote sensing tasks and regions, but their geographic
arXiv:2606.28992v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) have demonstrated strong abilities in opendomain question answering, information extraction, and text gen
arXiv:2406.05830v2 Announce Type: replace-cross Abstract: This paper presents a fully probabilistic approach for solving optimal experimental design problems under budget constraints. The experimental
arXiv:2602.18431v2 Announce Type: replace-cross Abstract: Motivated by the problem of assigning mediators to cases in the Kenyan judicial system, we study an online resource allocation problem where i
arXiv:2606.12191v1 Announce Type: cross Abstract: Environments serve as interactive systems for large language model (LLM) based agents across diverse scenarios and play a crucial role in driving the
arXiv:2512.15231v3 Announce Type: replace Abstract: The automated and intelligent processing of massive remote sensing (RS) datasets is critical in Earth observation (EO). Existing automated systems a
arXiv:2501.12178v2 Announce Type: replace Abstract: Medical imaging studies often rely on a single sample per subject, assuming it is representative of their physiological traits. However, variations
aside_block <ListValue: [StructValue([('title', 'Summary of today’s news'), ('body', <wagtail.rich_text.RichText object at 0x7fb0f516f910>), ('btn_text', ''), ('href', ''), ('image', None)])]> AI-powe
arXiv:2602.21450v2 Announce Type: replace Abstract: Many robotic systems allow independent control of position and orientation (pose), including omnidirectional aerial vehicles, underwater robots, and
Not content with its push into autonomous artificial intelligence workers, WisdomAI Inc. is bringing its comprehensive analytics capabilities to third-party software-as-a-service platforms with today’
arXiv:2602.05961v2 Announce Type: replace Abstract: Sampling from a distribution p(x) propto e^{-E(x)} known up to a normalising constant is an important and challenging problem in statistics. Recent
Agentic artificial intelligence startup Canyon Code stepped out of the shadows today after closing on a 5 million pre-seed funding round. Its mission is to give enterprises the granular controls requi
arXiv:2605.23936v1 Announce Type: new Abstract: This book presents a comprehensive and systematic survey of graph theory under uncertainty, with particular emphasis on the unifying role of the uncerta
arXiv:2508.17090v4 Announce Type: replace-cross Abstract: Ecological Momentary Assessment (EMA) studies enable the collection of high-frequency self-reports of suicidal thoughts and behaviors (STBs) v
arXiv:2605.22853v1 Announce Type: cross Abstract: Many modern datasets are large and carry complex structural relationships. Graph-based methods have traditionally been used to represent networked dat
arXiv:2502.13822v3 Announce Type: replace-cross Abstract: We establish novel and general high-dimensional concentration inequalities and Berry-Esseen bounds for vector-valued martingales induced by Ma
arXiv:2605.19646v1 Announce Type: cross Abstract: Advancements in clinical Brain-Computer Interfaces (BCIs) depend on precise and reliable signal interpretation. However, the high-dimensional and nois
arXiv:2408.12385v3 Announce Type: replace-cross Abstract: We study the problem of approximately recovering a probability distribution given noisy measurements of its Chebyshev polynomial moments. This
arXiv:2510.10140v2 Announce Type: replace Abstract: Deep learning-based weather forecasting (DLWF) models leverage past weather observations to generate future forecasts, supporting a wide range of do
arXiv:2309.01243v4 Announce Type: replace-cross Abstract: We investigate the privacy of {em any} algorithm whose outputs have Gaussian distribution. This work is motivated by the prevalence of such al
arXiv:2605.04229v1 Announce Type: new Abstract: In this work, a data-driven framework based on Phase-Field simulations data is proposed to highlight the capabilities of neural networks to ensure accur
arXiv:2605.01299v1 Announce Type: new Abstract: Geometric Algebra (GA) presents challenges to learners due to its highly abstract mathematical structure and complex operational rules, as translating a
arXiv:2605.00879v1 Announce Type: new Abstract: Rehabilitation aims to help patients with limited mobility regain their physical abilities through targeted movements, exercises, stimulation, and other
arXiv:2601.07476v2 Announce Type: replace Abstract: Autonomous nano-drones, powered by vision-based tiny machine learning (TinyML) models, are a novel technology gaining momentum thanks to their broad
Today at Google Cloud Next, we are unveiling a more proactive Gemini Cloud Assist, our AI-assisted cloud operations platform. This update shifts your Google Cloud operations from manual workflows to a
At Google Cloud Next, we’re announcing a range of compute capabilities to enable your core general purpose and AI workloads for the agentic world with higher performance and lower costs. Why it matter
arXiv:2512.23748v2 Announce Type: replace Abstract: For complex simulation problems, inferring parameters often precludes the use of classical likelihood-based techniques due to intractable likelihood
arXiv:2507.12475v2 Announce Type: replace-cross Abstract: The St. Petersburg paradox presents a longstanding challenge in decision theory: its classical expected value diverges, yet no correspondingly
arXiv:2306.02781v4 Announce Type: replace-cross Abstract: Generative artificial intelligence, and large language models in particular, have emerged as one of the most transformative paradigms in moder
arXiv:2608.10339v1 Announce Type: cross Abstract: Hospital quality improvement (QI) programs routinely face multiple candidate interventions to optimize hospital flow, but existing methods struggle to
arXiv:2608.08101v1 Announce Type: new Abstract: Generative AI has emerged as one of the most transformative forces in modern artificial intelligence, reshaping how we create, imagine, and interact wit
Nearly every major AI lab uses Google Cloud infrastructure, including for training of models, inference for agents, and new frontier research. Google Cloud also continues to be the platform of choice
arXiv:2608.03096v1 Announce Type: cross Abstract: Recent advances in video generation models have significantly intensified the deepfake threat, yet the current deepfake video detection benchmarks rem
arXiv:2608.01194v1 Announce Type: cross Abstract: Artificial intelligence has been transformed by deep neural networks, yet the search for new learning architectures continues. Quantum machine learnin
arXiv:2608.01544v1 Announce Type: cross Abstract: The CLIP Q-score is a novel, safe, fully reproducible, and computationally efficient method for extracting objective product quality metrics from visu
arXiv:2403.06494v2 Announce Type: replace-cross Abstract: This paper introduces a novel, lightweight method to solve the visibility problem for 2D grids. The proposed method evaluates the existence of
arXiv:2607.27295v1 Announce Type: cross Abstract: The rational design of photocatalysts for environmental remediation and CO2 conversion remains limited by the high computational cost and sparse exper
arXiv:2607.26241v1 Announce Type: cross Abstract: The Word Problem has been a subject of intensive mathematical study for over a century, initially driving advances in combinatorial group theory and m
arXiv:2607.25242v1 Announce Type: new Abstract: Medical world models offer a framework for extending medical artificial intelligence beyond static prediction by representing evolving patient states an
arXiv:2606.05202v2 Announce Type: replace-cross Abstract: In reactor physics, neutronics and multi-physics phenomena can be modelled at different fidelity levels. High-fidelity models based on the Bol
ML research is progressing at breakneck speed where frontier labs in both academia and industry have access to considerably large computes (GPUs). Where do small labs or independent researchers go in
The NVIDIA OptiX Toolkit (OTK) is a BSD 3‑clause licensed collection of utilities that provides unified, minimal‑macro error checking across OptiX, CUDA runtime, and CUDA driver APIs, generating diagn
arXiv:2607.19744v1 Announce Type: cross Abstract: The wind energy industry relies on accurate power curve models to make power forecast, evaluate turbine performance, quantify upgrade, or support site
arXiv:2607.19676v1 Announce Type: new Abstract: Civil aviation is safety critical and its operations, from flight decks and towers to ramps and maintenance, generate massive, heterogeneous data at the
arXiv:2607.13576v1 Announce Type: new Abstract: Interactive driving, wherein an intelligent lead vehicle equipped with real-time traffic data coordinates route choices of connected vehicles, offers a
arXiv:2607.11920v1 Announce Type: cross Abstract: Evaluating decisions made under uncertainty is hard when labeled outcomes are scarce, costly, or confounded with luck. We treat subjective expected ut
arXiv:2607.07236v1 Announce Type: new Abstract: This study investigates the presence and propagation of bias within Neural Networks through a comprehensive multi-level analysis spanning the learned la
arXiv:2607.04219v1 Announce Type: new Abstract: The integration of AI into Internet of Things (AIoT) systems has gradually transformed them from passive data collection infrastructures into intelligen
arXiv:2607.03211v1 Announce Type: new Abstract: Global navigation systems require state estimation algorithms that handle Earth's curvature, Earth's rotation, and gravitational variations. These facto
arXiv:2111.15255v2 Announce Type: replace-cross Abstract: The probabilistic linguistic term has been proposed to deal with probability distributions in provided linguistic evaluations. However, becaus
arXiv:2607.04431v1 Announce Type: cross Abstract: Quantile regression provides a powerful tool for summarizing the conditional distribution of a real valued random variable (r.v.) of interest Y as a f