Summary of Deep Analysis Of Time Series Data For Smart Grid Startup Strategies: a Transformer-lstm-pso Model Approach, by Zecheng Zhang
Deep Analysis of Time Series Data for Smart Grid Startup Strategies: A Transformer-LSTM-PSO Model Approachby…
Deep Analysis of Time Series Data for Smart Grid Startup Strategies: A Transformer-LSTM-PSO Model Approachby…
Focal Depth Estimation: A Calibration-Free, Subject- and Daytime Invariant Approachby Benedikt W. Hosp, Björn Severitt,…
HVM-1: Large-scale video models pretrained with nearly 5000 hours of human-like video databy A. Emin…
Comparison of different Artificial Neural Networks for Bitcoin price forecastingby Silas Baumann, Karl A. Busch,…
Predicting Stock Prices with FinBERT-LSTM: Integrating News Sentiment Analysisby Wenjun Gu, Yihao Zhong, Shizun Li,…
Enhancing Microgrid Performance Prediction with Attention-based Deep Learning Modelsby Vinod Kumar Maddineni, Naga Babu Koganti,…
X-Former: Unifying Contrastive and Reconstruction Learning for MLLMsby Sirnam Swetha, Jinyu Yang, Tal Neiman, Mamshad…
ColorMAE: Exploring data-independent masking strategies in Masked AutoEncodersby Carlos Hinojosa, Shuming Liu, Bernard GhanemFirst submitted…
Urban Traffic Forecasting with Integrated Travel Time and Data Availability in a Conformal Graph Neural…
Enhancing Multi-Step Brent Oil Price Forecasting with Ensemble Multi-Scenario Bi-GRU Networksby Mohammed Alruqimi, Luca Di…