<｜begin▁of▁sentence｜>### Instruction:
Given two small graphs, a star graph of size 4 and a cycle graph of size 5, how can the 'WaveletCharacteristic' model be used to get their embeddings based on the implementation from the CIKM ‘21 paper, and what are the embeddings?
### Response:
import networkx as nx
from karateclub import WaveletCharacteristic
import numpy as np

# Create two small NetworkX graphs
G1 = nx.star_graph(4)
G2 = nx.cycle_graph(5)

# Instantiate the WaveletCharacteristic with specified parameters
model = WaveletCharacteristic(order=5, eval_points=5, theta_max=2.5, tau=1.0, pooling='mean')

# Fit the model on a list of graphs
model.fit([G1, G2])

# Get the embeddings for the list of graphs
embeddings = model.get_embedding()

print(embeddings)
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