Nature

This AI model ‘studied’ physics — and learnt to forecast extreme weather

Combining artificial intelligence with a conventional climate model can predict heatwaves faster than the standard model ...
IEEE

The Research of Wind Farm Power Forecasting Based on VMD-IPSO-CNN-LSTM Hybrid Approach

Abstract: To enhance the accuracy and stability of wind-farm power forecasting, this study proposes a hybrid framework integrating Variational Mode Decomposition (VMD), an improved Particle Swarm ...
IEEE

Comparative Evaluation of LSTM, TCN, and Quantile Regression with Conformal Prediction for Time Series Forecasting under Uncertainty

Abstract: Accurate forecasting with uncertainty quantification is essential in high-risk time series applications. Conformal Prediction (CP) offers a model-agnostic way to generate valid prediction ...
GitHub

mohansree14/Bayesian-Deep-Learning-for-Probabilistic-Financial-Forecasting

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 ...