<｜begin▁of▁sentence｜>### Instruction:
Given a list of Erdős-Rényi graphs with 50 nodes and a probability of 0.1 for edge creation, can you use the WaveletCharacteristic model to generate an embedding for these graphs, considering the parameters stated in the 'WaveletCharacteristic' description from the API documentation?
### Response:
import networkx as nx
from karateclub import WaveletCharacteristic
import numpy as np

# Create sample graphs
G1 = nx.erdos_renyi_graph(n=50, p=0.1)
G2 = nx.erdos_renyi_graph(n=50, p=0.1)
graphs = [G1, G2]

# Initialize the WaveletCharacteristic model with default parameters
model = WaveletCharacteristic()

# Fit the model on the graph list
descriptors = model.fit(graphs)

# Retrieve the graph embedding
embedding = model.get_embedding()

print(embedding)
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