Kenzhebek Y 1

1. A Systematic Analysis of Physics-Informed Neural Networks for Two-Phase Flow with Capillarity: The Muskat–Leverett Problem
2. Enhancing Oil Recovery Predictions by Leveraging Polymer Flooding Simulations and Machine Learning Models on a Large-Scale Synthetic Dataset
3. Performance and stability of physics-informed Kolmogorov-Arnold networks for two-phase transport in porous media: A comparative study with physics-informed neural networks
4. Coupled pressure and saturation prediction for two-phase flow in porous media using physics-informed neural networks (PINNs)
5. IMPLEMENTATION OF REGRESSION ALGORITHMS FOR OIL RECOVERY PREDICTION
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