How can we be sure that there is sufficient data for our model, such that the predictions remain reliable on unseen data and the conclusions drawn from the fitted model would not vary significantly ...

Previous studies have established a relationship between duodenal mucosa-associated microbiota and overall health. However, sampling duodenal microbiota is technically challenging. Mucosal biopsies ...

Abstract: Real-world optimization problems often come with constraints that limit the feasibility of solutions, posing challenges for finding viable solutions. While various constraint handling ...

Denoising Diffusion Probabilistic Models (DDPMs) have gained great attention in adversarial purification. Current diffusion-based works focus on designing effective condition-guided mechanisms while ...

Abstract: The explosive growth of social media platforms has generated vast amounts of interaction data, presenting both opportunities and challenges for researchers and analysts. Effective random ...

In a study published in PNAS, a research team developed a new reinforcement learning-based enhanced sampling method called Adaptive Collective Variables Generator (Adaptive CVgen), which has been ...

A weighted random item sampler (selector), where the probability of selecting an item is proportional to its weight, and every item is sampled exactly once (without repetition or replacement). The ...

Quantum computers are a revolutionary technology that harnesses the principles of quantum mechanics to perform calculations that would be infeasible for classical computers. Evaluating the performance ...