53 citations · 57 across the 9 of their papers we have counts for
4 papers · 1 filter
Evolutionary Two-Stage Hyperparameter Optimization Strategies for Physics-Informed Neural Networks
Fedor Buzaev, Dmitry Efremenko, Egor Bugaev +4
Physics-Informed Neural Networks (PINNs) solve Partial Differential Equations (PDEs) by embedding physical laws into neural network training. However, their performance suffers fro…
Correcting Sensor-Induced Distribution Drift with Wasserstein Adversarial Learning
Saraa Ali, Vladimir Bocharnikov, Fedor Ratnikov +3
The quality of recorded data depends on the stability of the sensor system that acquires it. Sensor motion and aging can degrade the performance and stability of downstream data-dr…
Physics-Constrained Neural Networks for Improved Short-Term Weather Forecasting: A Case Study over the South Pacific
Egor Bugaev, Fedor Buzaev, Dmitry Efremenko +2
This study introduces enhancements to physics-constrained neural networks (PCNNs) that improve the accuracy and stability of hybrid short-term weather forecasting models. Building…
RL-ABC: Reinforcement Learning for Accelerator Beamline Control
Anwar Ibrahim, Fedor Ratnikov, Maxim Kaledin +2
Particle accelerator beamline optimization is a high-dimensional control problem traditionally requiring significant expert intervention. We present RLABC (Reinforcement Learning f…