![MiniRocket and Global Pooling exhibit contrasting performance based on phylogenetic distance, with MiniRocket maintaining accuracy across increasing distances on validation sets while Global Pooling excels on unseen test sets, demonstrating that antibiotic resistance mechanisms-rather than phylogenetic relatedness alone-are the primary determinants of predictive power in assessing ampicillin resistance, a finding consistently observed across replicate analyses and further substantiated by metrics such as Matthews correlation coefficient [latex] MCC [/latex].](https://arxiv.org/html/2603.11141v1/figures/ampicillin_v1-1_phylogenetic_distance.png)
New research reveals that the key to accurately forecasting antibiotic resistance across different bacteria lies in how genomic information is analyzed, matching the method to the underlying genetic mechanisms.
A new framework leverages the underlying connections between different incidents to more accurately reconstruct what’s happening in a city based on resident reports.
As complex engineering systems grow, distributing control via multi-agent reinforcement learning offers scalability, but new research reveals this can come at the expense of optimal performance.
New research demonstrates how analyzing doctor’s notes with advanced AI can forecast patient response to chemotherapy, potentially personalizing cancer treatment.
Researchers have developed VisiFold, a novel framework that leverages graph-based techniques to dramatically improve the accuracy and efficiency of forecasting traffic patterns over extended periods.
![The equilibrium mean control [latex]\bar{D}^{1}(t)[/latex] is demonstrably affected by signal precision [latex]p[/latex], exhibiting a heightened incentive for belief manipulation when precision is low due to sluggish opponent posteriors, and converging towards a perfect-information benchmark as [latex]p[/latex] approaches infinity.](https://arxiv.org/html/2603.12140v1/x3.png)
New research reveals how strategic players can both predict and influence the expectations of others, with significant implications for economic efficiency.
This review explores a novel architecture for managing decentralized AI workloads across dynamic, multi-domain environments.
A new approach leverages the power of artificial intelligence to streamline the complex tasks of managing and maintaining modern optical networks.
New research reveals how cognitive biases impact the accuracy of human-annotated data for rare-event AI, and proposes effective strategies to counteract them.
This review explores the methods used to quantify trust within the complex networks of online social platforms.