109

arXiv:2106.12905v2 Announce Type: replace
Abstract: Background: Early forecasts of dengue are an important tool for disease mitigation. Neural networks are powerful predictive models that have made contributions to many areas of public health. In this study, we reviewed the application of neural ne…
230

A new stem cell–based therapy challenges traditional pain treatment by using pain-sensing neurons to reduce inflammation and protect joints. Newly released preclinical data describes an unconventional strategy for managing chronic pain while helping preserve joint tissue. The findings focus on SN101…
322

arXiv:2512.16269v1 Announce Type: new
Abstract: We introduce a numerical framework for reconstructing the potential in two dimensional semilinear elliptic PDEs with power type nonlinearities from the nonlinear Dirichlet to Neumann map. By applying higher order linearization method, we compute the F…
109

arXiv:2512.15767v1 Announce Type: new
Abstract: Simulating complex unsteady physical phenomena relies on detailed mathematical models, simulated for instance by using the Finite Element Method (FEM). However, these models often exhibit discrepancies from the reality due to unmodeled effects or simp…
108

arXiv:2512.16624v1 Announce Type: new
Abstract: Learning-based model predictive control has emerged as a powerful approach for handling complex dynamics in mechatronic systems, enabling data-driven performance improvements while respecting safety constraints. However, when computational resources a…
109

Abstract
We present a suite of algorithmic techniques for handling substitution tilings by treating a tile's hierarchy of supertiles in a purely combinatorial fashion using finite state automata. The resulting techniques are very convenient for practical generation of patches of tilings such as hats…
321

arXiv:2510.15610v2 Announce Type: replace-cross
Abstract: We revisit random search for stochastic optimization, where only noisy function evaluations are available. We show that the method works under weaker smoothness assumptions than previously considered, and that stronger assumptions enable imp…
212

arXiv:2512.16872v1 Announce Type: new
Abstract: Inspired by biology, spiking neural networks (SNNs) process information via discrete spikes over time, offering an energy-efficient alternative to the classical computing paradigm and classical artificial neural networks (ANNs). In this work, we analy…
111

arXiv:2512.16023v1 Announce Type: new
Abstract: We present a method to generate video-action pairs that follow text instructions, starting from an initial image observation and the robot's joint states. Our approach automatically provides action labels for video diffusion models, overcoming the com…
220

arXiv:2512.16875v1 Announce Type: new
Abstract: We study the problem of finding confidence ellipsoids for an arbitrary distribution in high dimensions. Given samples from a distribution $D$ and a confidence parameter $\alpha$, the goal is to find the smallest volume ellipsoid $E$ which has probabil…
130

arXiv:2502.10239v2 Announce Type: replace
Abstract: Federated fine-tuning offers a promising approach for tuning Large Language Models (LLMs) on edge devices while preserving data privacy. However, fine-tuning these models on edge devices remains challenging due to high memory, communication, and c…