Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...
Climate and ocean models use a series of equations to represent complex natural processes. However, the equations used in ...
Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...
A systematic review newly published in the Journal of Pipeline Science and Engineering maps machine learning (ML) advances for pipelines across the full lifecycle: reliability-based design, structural ...
Abstract: Extreme learning machine (ELM) has become a popular topic in machine learning in recent years. ELM is a new kind of single-hidden layer feedforward neural network with an extremely low ...
Imagine a scenario where a team of doctors faces a perplexing medical puzzle. A patient shows a range of symptoms, each pointing to multiple possible diseases. How can they navigate this diagnostic ...
The behavior of language models is influenced by the prior context provided in prompts. Depending on whether you pick synthesis or shake, the next row looks very different — Vishal Misra Contextual ...
Baal is an active learning library that supports both industrial applications and research usecases. Read the documentation at https://baal.readthedocs.io. Our paper can be read on arXiv. It includes ...
Abstract: Multiple-instance learning (MIL) can solve supervised learning tasks, where only a bag of multiple instances is labeled, instead of a single instance. It is considerably important to develop ...
This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...
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