fix(model):ODE-based models info

Author: Ladbaby

models/GNeuralFlow.py

@@ -21,6 +21,8 @@ class Model(nn.Module):
     - paper: "Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series" (NeurIPS 2024)
     - paper link: https://openreview.net/forum?id=tFB5SsabVb
     - Code adapted from: https://github.com/gmerca/GNeuralFlow
+
+    Note: PyOmniTS has optimized its implementation for speed.
     '''
     def __init__(self, configs: ExpConfigs):
         super(Model, self).__init__()

models/Latent_ODE.py

@@ -19,6 +19,8 @@ class Model(nn.Module):
     - paper: "Latent Ordinary Differential Equations for Irregularly-Sampled Time Series" (NeurIPS 2019)
     - paper link: https://papers.nips.cc/paper_files/paper/2019/hash/42a6845a557bef704ad8ac9cb4461d43-Abstract.html
     - Code adapted from: https://github.com/YuliaRubanova/latent_ode
+
+    Note: PyOmniTS has optimized its implementation for speed.
     '''
     def __init__(self, configs: ExpConfigs):
         super(Model, self).__init__()

models/NeuralFlows.py

@@ -21,6 +21,8 @@ class Model(nn.Module):
     - paper: "Neural Flows: Efficient Alternative to Neural ODEs" (NeurIPS 2021)
     - paper link: https://proceedings.neurips.cc/paper/2021/hash/b21f9f98829dea9a48fd8aaddc1f159d-Abstract.html
     - Code adapted from: https://github.com/mbilos/neural-flows-experiments
+
+    Note: PyOmniTS has optimized its implementation for speed.
     '''
     def __init__(self, configs: ExpConfigs):
         super(Model, self).__init__()