Plus: dynamic multi frame generation that adjusts itself to your monitor's refresh rate.

Nvidia announced DLSS 4.5 at CES today, an update to its deep learning super sampling (DLSS) feature that improves image ...
IEEE

ABMF-Net: An Attentive Bayesian Multi-Stage Deep Learning Model for Robust Forecasting of Electricity Price and Demand

Abstract: This article presents a novel deep learning model, the Attentive Bayesian Multi-Stage Forecasting Network (ABMF-Net), designed for robust forecasting of electricity price (USD/MWh) and ...
Devdiscourse

Sophisticated AI promising but less reliable for monetary policy decisions

The study, titled Reinforcement Learning for Monetary Policy Under Macroeconomic Uncertainty: Analyzing Tabular and Function ...
Frontiers

Enhancing disaster prediction with Bayesian deep learning: a robust approach for uncertainty estimation

Accurate disaster prediction combined with reliable uncertainty quantification is crucial for timely and effective decision-making in emergency management. However, traditional deep learning methods ...
IEEE

Bayesian Deep Learning for Fault Diagnosis of Induction Motors With Reduced Data Reliance and Improved Interpretability

Abstract: Fault diagnosis holds significant practical importance for high performance and reliable control of induction motors. However, existing deep learning-based fault diagnosis methods demand a ...
marktechpost

BEAL: A Bayesian Deep Active Learning Method for Efficient Deep Multi-Label Text Classification

Multi-label text classification (MLTC) assigns multiple relevant labels to a text. While deep learning models have achieved state-of-the-art results in this area, they require large amounts of labeled ...
Frontiers

Bayesian reinforcement learning for navigation planning in unknown environments

This study focuses on a rescue mission problem, particularly enabling agents/robots to navigate efficiently in unknown environments. Technological advances, including manufacturing, sensing, and ...
marktechpost

Advances in Bayesian Deep Neural Network Ensembles and Active Learning for Preference Modeling

Machine learning has seen significant advancements in integrating Bayesian approaches and active learning methods. Two notable research papers contribute to this development: “Bayesian vs.