Stay updated with the latest research and technology news
arXiv:2509.22341v2 Announce Type: replace-cross Abstract: Model collapse occurs when generative models degrade after repeatedly training on their own synthetic outputs. We study this effect in...
arXiv:2509.16301v2 Announce Type: replace-cross Abstract: Integration and analysis of multi-omics data provide valuable insights for improving cancer subtype classification. However, such data are inherently heterogeneous,...
arXiv:2508.17655v5 Announce Type: replace-cross Abstract: Nonlinear dynamical systems with continuous variables can be used for solving combinatorial optimization problems with discrete variables. Numerical simulations of...
arXiv:2507.22509v2 Announce Type: replace-cross Abstract: In 2012, Ne\v{s}et\v{r}il and Ossona de Mendez proved that graphs of bounded degeneracy that have a path of order $n$...
arXiv:2507.11779v4 Announce Type: replace-cross Abstract: We consider a class of multi-agent distributed synchronization systems, which are modeled as $n$ particles moving on the real line....
arXiv:2507.02890v3 Announce Type: replace-cross Abstract: In Industry 4.0 manufacturing environments, forecasting Overall Equipment Efficiency (OEE) is critical for data-driven operational control and predictive maintenance. However,...
arXiv:2506.22488v2 Announce Type: replace-cross Abstract: Accurate decoding of lower-limb motion from EEG signals is essential for advancing brain-computer interface (BCI) applications in movement intent recognition...
arXiv:2506.18846v2 Announce Type: replace-cross Abstract: In many inverse problems, the unknown is composed of multiple components with different regularities, for example, in imaging problems, where...
arXiv:2506.18314v2 Announce Type: replace-cross Abstract: Foundation models are transforming neuroscience but are often prohibitively large, data-hungry, and difficult to deploy. Here, we introduce BrainSymphony, a...
arXiv:2505.18362v2 Announce Type: replace-cross Abstract: We develop a general theoretical framework for optimal probability density control on standard measure spaces, aimed at addressing large-scale multi-agent...
arXiv:2505.13732v5 Announce Type: replace-cross Abstract: We introduce $\textit{Backward Conformal Prediction}$, a method that guarantees conformal coverage while providing flexible control over the size of prediction...
arXiv:2505.07078v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have recently been leveraged for asset pricing tasks and stock trading applications, enabling AI agents to...
arXiv:2504.06475v2 Announce Type: replace-cross Abstract: Tensor networks like matrix product states (MPSs) and matrix product operators (MPOs) are powerful tools for representing exponentially large states...
arXiv:2504.03757v2 Announce Type: replace-cross Abstract: Decoding gait dynamics from EEG signals presents significant challenges due to the complex spatial dependencies of motor processes, the need...
arXiv:2501.02942v3 Announce Type: replace-cross Abstract: Building on the blueprint from Goemans and Williamson (1995) for the Max-Cut problem, we construct a polynomial-time approximation algorithm for...
arXiv:2412.10251v2 Announce Type: replace-cross Abstract: We present a novel, model-free, and data-driven methodology for controlling complex dynamical systems into previously unseen target states, including those...
arXiv:2409.17525v3 Announce Type: replace-cross Abstract: Spoken language is often, if not always, understood in a context formed by the identity of the speaker. For example,...
arXiv:2409.01869v3 Announce Type: replace-cross Abstract: For optimization models to be used in practice, it is crucial that users trust the results. A key factor in...
arXiv:2404.18104v2 Announce Type: replace-cross Abstract: The relevance of shallow-depth quantum circuits has recently increased, mainly due to their applicability to near-term devices. In this context,...
arXiv:2403.17770v3 Announce Type: replace-cross Abstract: Despite the significant success achieved by deep learning methods in medical image segmentation, researchers still struggle in the computer-aided diagnosis...
arXiv:2309.04414v3 Announce Type: replace-cross Abstract: The expectation that scientific productivity follows regular patterns over a career underpins many scholarly evaluations. However, recent studies of individual...
arXiv:2306.14851v4 Announce Type: replace-cross Abstract: Given a high-dimensional covariate matrix and a response vector, ridge-regularized sparse linear regression selects a subset of features that explains...
arXiv:2211.03997v3 Announce Type: replace-cross Abstract: Online platforms increasingly rely on sequential decision-making algorithms to allocate resources, match users, or control exposure, while facing growing pressure...
arXiv:2106.14010v4 Announce Type: replace-cross Abstract: In 2019 P. Patak and M. Tancer obtained the following higher-dimensional generalization of the Heawood inequality on embeddings of graphs...