Predictive Modeling: Techniques, Uses, and Key Takeaways

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
Scientific Research Publishing

Applying Deep Learning Techniques for Automated Analysis and Interpretation of Financial Statements ()

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...
IEEE

Improving Floating Offshore Wind Farm Flow Control With Scalable Model-Based Deep Reinforcement Learning

Abstract: This paper proposes a model-based deep reinforcement learning (DRL) framework to maximize the total power output and minimize the fatigue load of a floating offshore wind farm subject to ...
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
NFL

Next Gen Stats: New advanced metrics you NEED to know for the 2025 NFL season

Since the inception of Next Gen Stats, we have relied on the basic logic of crediting a target in coverage to the closest defender to the receiver when the pass arrives. This method was directionally ...
GitHub

Deep Learning Classification for IPO Performance Prediction

This project demonstrates building a deep learning classification model using TensorFlow/Keras to predict whether an Initial Public Offering (IPO) will list at a profit or loss. The dataset contains ...
Sports Illustrated

Raiders Training Camp Report No. 14: Deep Dive on the New Depth Chart

Our latest episode of the Las Vegas Raiders Insider Podcast offers a deep dive look at today's practice and the latest Silver and Black depth chart. HENDERSON, Nev.—The Las Vegas Raiders moved indoors ...
Frontiers

Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
Frontiers

BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers

Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...
IEEE

Comparison of Deep-Learning Models for Classification of Cellular Phenotype From Flow Cytometry Data

Abstract: This study compares the relative utility of deep learning models as automated phenotypic classifiers, built with features of peripheral blood cell populations assayed with flow cytometry. We ...