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Fix LaTeX notation and update print statement
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docs/notebooks/linear_gaussian_ssm/lgssm_learning.ipynb

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@@ -12,8 +12,8 @@
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"\n",
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"Here, we work with simulated noisy data from an LG-SSM with known parameters, and then we see how well we can recover the true parameters and states given the observations. The model is,\n",
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"\\begin{align*}\n",
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"z_{t+1} \\mid z_t, \\theta &\\sim \\mathrm{N}(F z_t, Q) \\\\\n",
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"y_t \\mid z_t, \\theta &\\sim \\mathrm{N}(H z_t, R)\n",
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"z_{t+1} \\mid z_t, \\theta &\\sim \\mathcal{N}(F z_t, Q) \\\\\n",
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"y_t \\mid z_t, \\theta &\\sim \\mathcal{N}(H z_t, R)\n",
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"\\end{align*}\n",
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"where $z_{1:T}$ are the latent states, $y_{1:T}$ are the emissions, and $\\theta = (F, Q, H, R)$ are the model parameters. In particular, $F$ is the dynamics matrix and $H$ is the emission matrix. For our simulation, we use 2-dimensional latent states, $z_t \\in \\mathbb{R}^2$, and 10-dimensional emissions, $y_t \\in \\mathbb{R}^{10}$. \n",
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"\n",
@@ -542,7 +542,7 @@
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"sgd_params, sgd_param_props = model.initialize(\n",
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" init_key, dynamics_weights=true_A, dynamics_covariance=true_Sigma)\n",
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"\n",
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"print(f\"freeing the dynamics matrix to:\\n {sgd_params.dynamics.weights}\")\n",
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"print(f\"freezing the dynamics matrix to:\\n {sgd_params.dynamics.weights}\")\n",
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"sgd_param_props.dynamics.weights.trainable = False\n",
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"sgd_param_props.dynamics.cov.trainable = False\n",
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"\n",

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