surrogate-modeling

Python Low-Code System Solutions

Official repo for "The impact of internal variability on benchmarking deep learning climate emulators" in JAMES25 (public)

A Genetic Algorithm (GA) / Discrete Particle Swarm Optimization/ Hybrid (GA-PSO) for nuclear fuel optimization using ML surrogates (DNN, KNN, Random Forest, Ridge) and OpenMC. Optimizes fuel loading patterns for a target k-eff and minimal Power Peaking Factor (PPF).

Modern OpenTURNS web workspace for reproducible uncertainty quantification, sensitivity analysis, reliability, surrogates, and traceable reports.

Performance Modeling of Data Storage Systems Using Generative Models, IEEE Access, vol. 13, pp. 49643-49658, 2025, doi: 10.1109/ACCESS.2025.3552409

This repository provides an implementation of algorithmic support for dynamic pricing based on surrogate ticket demand modeling for a passenger rail company on open data.

A novel neural network for effective learning of highly impulsive/oscillatory dynamic systems by jointly utilizing low-order derivatives

The last few solves you'll ever pay for: certified accelerator + identification layer over any black-box parametric solver, built on resona's effective-rank dial.

ReservoirNeuralBench – A controlled benchmark of neural surrogates for 3D reservoir simulation on the Norne field.

基于实验数据标定的P2D电化学模型，结合机器学习代理模型（GPR）与 NSGA-II 遗传算法，对磷酸铁锂（LFP）电池的比能量（SE）—比功率（SP）进行多目标优化，求解 Pareto 前沿。

Physics-constrained TMM-SVR surrogate pipeline for PDMS thin-film infrared emissivity prediction

Thermophysical data workbench for generating, importing, comparing, validating and visualizing data from experiments, literature, property models and simulation backends, with leakage-aware preparation for physics-informed machine learning.

Uncertainty quantification, Bayesian inference, and scientific ML for physical/biological models

Python code for running the numerical experiments in the paper "Neural Network Accelerated Implicit Filtering: Integrating Neural Network Surrogates With Provably Convergent Derivative Free Optimization Methods" by Brian Irwin, Eldad Haber, Raviv Gal, and Avi Ziv.

Open benchmark of FNO, conditional-diffusion (U-Net & DiT), and ensemble-UQ surrogates for two-phase porous-media flow (CO2 sequestration).

Official code for "Data-Driven Prediction of Stress–Strain Fields Around Interacting Mining Excavations". Uses FEM data & Machine Learning (RF, LightGBM, CatBoost, MLP).

Monte Carlo neutron transport simulation with neural-network surrogate models for fast transmission prediction.

Uncertainty Quantification pipeline for reinforced-concrete FEM (Abaqus) using surrogate models (PCA+GPR, AE+GPR, Shape-Scale) for fast Monte Carlo propagation, sensitivity analysis, and reliability metrics.

BathySurrogate: An Open-Source Environmental Surrogate Framework for Satellite-Derived Bathymetry via Multi-Source Data Fusion and Spatial Validation

CARDIOKOOP - Control-aware Koopman deep learning framework for real-time hemodynamic forecasting and cardiovascular digital twin applications.