# Core scientific computing
numpy>=1.21.0
pandas>=1.3.0
scikit-learn>=1.0.0

# Deep learning
torch>=1.10.0
torchvision>=0.11.0

# Official KAN library
pykan>=0.1.0

# Bayesian optimization
optuna>=3.0.0

# Progress bars
tqdm>=4.62.0

# Evolutionary algorithms
deap>=1.3.0

# Plotting (optional)
matplotlib>=3.5.0
seaborn>=0.11.0

# Data processing
scipy>=1.7.0

# Gradient boosting
xgboost>=1.5.0

# Note: datetime, json, argparse, warnings are built-in Python modules