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    "brulee_auto_int",
    "brulee_chronos",
    "brulee_linear_reg",
    "brulee_logistic_reg",
    "brulee_mlp",
    "brulee_mlp_two_layer",
    "brulee_multinomial_reg",
    "brulee_resnet",
    "brulee_rln",
    "brulee_saint",
    "brulee_tab_icl",
    "brulee_tab_pfn",
    "coef",
    "matrix_to_dataset",
    "schedule_cyclic",
    "schedule_decay_expo",
    "schedule_decay_time",
    "schedule_step",
    "set_learn_rate",
    "tab_icl_download_weights",
    "tab_icl_weights_available",
    "tab_pfn_clear_cache",
    "tab_pfn_download_weights",
    "tab_pfn_versions",
    "tab_pfn_weights_available",
    "tunable"
  ],
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    {
      "page": "brulee_activations",
      "title": "Activation functions for neural networks in brulee",
      "topics": [
        "brulee_activations"
      ]
    },
    {
      "page": "brulee_auto_int",
      "title": "Fit AutoInt models for tabular data",
      "topics": [
        "brulee_auto_int",
        "brulee_auto_int.data.frame",
        "brulee_auto_int.default",
        "brulee_auto_int.formula",
        "brulee_auto_int.matrix",
        "brulee_auto_int.recipe"
      ]
    },
    {
      "page": "brulee_chronos",
      "title": "Use a Chronos-2 tabular foundation model",
      "topics": [
        "brulee_chronos",
        "brulee_chronos.data.frame",
        "brulee_chronos.default",
        "brulee_chronos.formula",
        "brulee_chronos.recipe"
      ]
    },
    {
      "page": "brulee_linear_reg",
      "title": "Fit a linear regression model",
      "topics": [
        "brulee_linear_reg",
        "brulee_linear_reg.data.frame",
        "brulee_linear_reg.default",
        "brulee_linear_reg.formula",
        "brulee_linear_reg.matrix",
        "brulee_linear_reg.recipe"
      ]
    },
    {
      "page": "brulee_logistic_reg",
      "title": "Fit a logistic regression model",
      "topics": [
        "brulee_logistic_reg",
        "brulee_logistic_reg.data.frame",
        "brulee_logistic_reg.default",
        "brulee_logistic_reg.formula",
        "brulee_logistic_reg.matrix",
        "brulee_logistic_reg.recipe"
      ]
    },
    {
      "page": "brulee_mlp",
      "title": "Fit neural networks",
      "topics": [
        "brulee_mlp",
        "brulee_mlp.data.frame",
        "brulee_mlp.default",
        "brulee_mlp.formula",
        "brulee_mlp.matrix",
        "brulee_mlp.recipe",
        "brulee_mlp_two_layer",
        "brulee_mlp_two_layer.data.frame",
        "brulee_mlp_two_layer.default",
        "brulee_mlp_two_layer.formula",
        "brulee_mlp_two_layer.matrix",
        "brulee_mlp_two_layer.recipe"
      ]
    },
    {
      "page": "brulee_multinomial_reg",
      "title": "Fit a multinomial regression model",
      "topics": [
        "brulee_multinomial_reg",
        "brulee_multinomial_reg.data.frame",
        "brulee_multinomial_reg.default",
        "brulee_multinomial_reg.formula",
        "brulee_multinomial_reg.matrix",
        "brulee_multinomial_reg.recipe"
      ]
    },
    {
      "page": "brulee_resnet",
      "title": "Fit residual neural networks (ResNet)",
      "topics": [
        "brulee_resnet",
        "brulee_resnet.data.frame",
        "brulee_resnet.default",
        "brulee_resnet.formula",
        "brulee_resnet.matrix",
        "brulee_resnet.recipe"
      ]
    },
    {
      "page": "brulee_rln",
      "title": "Fit Regularization Learning Networks (RLN)",
      "topics": [
        "brulee_rln",
        "brulee_rln.data.frame",
        "brulee_rln.default",
        "brulee_rln.formula",
        "brulee_rln.matrix",
        "brulee_rln.recipe"
      ]
    },
    {
      "page": "brulee_saint",
      "title": "Fit SAINT models for tabular data",
      "topics": [
        "brulee_saint",
        "brulee_saint.data.frame",
        "brulee_saint.default",
        "brulee_saint.formula",
        "brulee_saint.matrix",
        "brulee_saint.recipe"
      ]
    },
    {
      "page": "brulee_tab_icl",
      "title": "Use a TabICL tabular foundation model",
      "topics": [
        "brulee_tab_icl",
        "brulee_tab_icl.data.frame",
        "brulee_tab_icl.default",
        "brulee_tab_icl.formula",
        "brulee_tab_icl.matrix",
        "brulee_tab_icl.recipe"
      ]
    },
    {
      "page": "brulee_tab_pfn",
      "title": "Use a TabPFN tabular foundation model",
      "topics": [
        "brulee_tab_pfn",
        "brulee_tab_pfn.data.frame",
        "brulee_tab_pfn.default",
        "brulee_tab_pfn.formula",
        "brulee_tab_pfn.matrix",
        "brulee_tab_pfn.recipe"
      ]
    },
    {
      "page": "brulee-augment",
      "title": "Add model predictions to data",
      "topics": [
        "augment.brulee_auto_int",
        "augment.brulee_chronos",
        "augment.brulee_linear_reg",
        "augment.brulee_logistic_reg",
        "augment.brulee_mlp",
        "augment.brulee_multinomial_reg",
        "augment.brulee_resnet",
        "augment.brulee_rln",
        "augment.brulee_saint",
        "augment.brulee_tab_icl",
        "augment.brulee_tab_pfn",
        "brulee-augment"
      ]
    },
    {
      "page": "brulee-autoplot",
      "title": "Plot model loss over epochs",
      "topics": [
        "autoplot.brulee_auto_int",
        "autoplot.brulee_linear_reg",
        "autoplot.brulee_logistic_reg",
        "autoplot.brulee_mlp",
        "autoplot.brulee_multinomial_reg",
        "autoplot.brulee_resnet",
        "autoplot.brulee_rln",
        "autoplot.brulee_saint",
        "brulee-autoplot"
      ]
    },
    {
      "page": "brulee-coefs",
      "title": "Extract Model Coefficients",
      "topics": [
        "brulee-coefs",
        "coef.brulee_linear_reg",
        "coef.brulee_logistic_reg",
        "coef.brulee_mlp",
        "coef.brulee_multinomial_reg",
        "coef.brulee_resnet",
        "coef.brulee_rln"
      ]
    },
    {
      "page": "matrix_to_dataset",
      "title": "Convert data to torch format",
      "topics": [
        "matrix_to_dataset"
      ]
    },
    {
      "page": "predict.brulee_auto_int",
      "title": "Predict from a 'brulee_auto_int'",
      "topics": [
        "predict.brulee_auto_int"
      ]
    },
    {
      "page": "predict.brulee_chronos",
      "title": "Predict from a 'brulee_chronos' model",
      "topics": [
        "predict.brulee_chronos"
      ]
    },
    {
      "page": "predict.brulee_linear_reg",
      "title": "Predict from a 'brulee_linear_reg'",
      "topics": [
        "predict.brulee_linear_reg"
      ]
    },
    {
      "page": "predict.brulee_logistic_reg",
      "title": "Predict from a 'brulee_logistic_reg'",
      "topics": [
        "predict.brulee_logistic_reg"
      ]
    },
    {
      "page": "predict.brulee_mlp",
      "title": "Predict from a 'brulee_mlp'",
      "topics": [
        "predict.brulee_mlp"
      ]
    },
    {
      "page": "predict.brulee_multinomial_reg",
      "title": "Predict from a 'brulee_multinomial_reg'",
      "topics": [
        "predict.brulee_multinomial_reg"
      ]
    },
    {
      "page": "predict.brulee_resnet",
      "title": "Predict from a 'brulee_resnet'",
      "topics": [
        "predict.brulee_resnet"
      ]
    },
    {
      "page": "predict.brulee_rln",
      "title": "Predict from a 'brulee_rln'",
      "topics": [
        "predict.brulee_rln"
      ]
    },
    {
      "page": "predict.brulee_saint",
      "title": "Predict from a 'brulee_saint'",
      "topics": [
        "predict.brulee_saint"
      ]
    },
    {
      "page": "predict.brulee_tab_icl",
      "title": "Predict from a 'brulee_tab_icl'",
      "topics": [
        "predict.brulee_tab_icl"
      ]
    },
    {
      "page": "predict.brulee_tab_pfn",
      "title": "Predict from a 'brulee_tab_pfn'",
      "topics": [
        "predict.brulee_tab_pfn"
      ]
    },
    {
      "page": "schedule_decay_time",
      "title": "Change the learning rate over time",
      "topics": [
        "schedule_cyclic",
        "schedule_decay_expo",
        "schedule_decay_time",
        "schedule_step",
        "set_learn_rate"
      ]
    },
    {
      "page": "summary.brulee",
      "title": "Summarize the architecture of a brulee model",
      "topics": [
        "summary.brulee",
        "summary.brulee_auto_int",
        "summary.brulee_mlp",
        "summary.brulee_resnet",
        "summary.brulee_rln",
        "summary.brulee_saint"
      ]
    },
    {
      "page": "tab_icl_download_weights",
      "title": "Download and cache pretrained TabICL weights",
      "topics": [
        "tab_icl_download_weights",
        "tab_icl_weights_available"
      ]
    },
    {
      "page": "tab_pfn_clear_cache",
      "title": "Remove cached TabPFN weights",
      "topics": [
        "tab_pfn_clear_cache"
      ]
    },
    {
      "page": "tab_pfn_download_weights",
      "title": "Download and cache pretrained TabPFN weights",
      "topics": [
        "tab_pfn_download_weights",
        "tab_pfn_weights_available"
      ]
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