diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt index 38ed3f55..fc9304ef 100644 --- a/_sources/index.rst.txt +++ b/_sources/index.rst.txt @@ -58,7 +58,7 @@ Get started * API (advanced): :ref:`api`. .. toctree:: - :maxdepth: 4 + :maxdepth: 1 :caption: Contents: intro.rst diff --git a/index.html b/index.html index 00c07a5d..d5f985c1 100644 --- a/index.html +++ b/index.html @@ -122,93 +122,10 @@

Get started

Contents:

 diff --git a/searchindex.js b/searchindex.js index f170e44f..9f456c71 100644 --- a/searchindex.js +++ b/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": [".ipynb_checkpoints/demos-checkpoint", ".ipynb_checkpoints/index-checkpoint", "API_demo/API_10_device", "API_demo/API_1_indexing", "API_demo/API_2_plotting", "API_demo/API_3_grid", "API_demo/API_4_extract_activations", "API_demo/API_5_initialization_hyperparameter", "API_demo/API_6_training_hyperparameter", "API_demo/API_7_pruning", "API_demo/API_8_checkpoint", "API_demo/API_9_video", "Examples/Example_10_relativity-addition", "Examples/Example_11_encouraing_linear", "Examples/Example_12_unsupervised_learning", "Examples/Example_13_phase_transition", "Examples/Example_1_function_fitting", "Examples/Example_2_deep_formula", "Examples/Example_3_classfication", "Examples/Example_4_symbolic_regression", "Examples/Example_5_special_functions", "Examples/Example_6_PDE", "Examples/Example_7_continual_learning", 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"demo-5-initialization-hyperparamters"]], "Demo 6: Training Hyperparamters": [[8, "demo-6-training-hyperparamters"]], "Parameter 1: \\lambda, overall penalty strength.": [[8, "parameter-1-lambda-overall-penalty-strength"]], "Parameter 2: (relative) penalty strength of entropy \\lambda_{\\rm ent}.": [[8, "parameter-2-relative-penalty-strength-of-entropy-lambda-rm-ent"]], "Parameter 3: Grid size G.": [[8, "parameter-3-grid-size-g"]], "Parameter 4: seed.": [[8, "parameter-4-seed"]], "Demo 7: Pruning": [[9, "demo-7-pruning"]], "Automatic pruning": [[9, "automatic-pruning"]], "Manual pruning": [[9, "manual-pruning"]], "Demo 8: Checkpoint": [[10, "demo-8-checkpoint"]], "Demo 9: Videos": [[11, "demo-9-videos"]], "Example 10: Use of lock for Relativity Addition": [[12, "example-10-use-of-lock-for-relativity-addition"]], "Example 11: Encouraging linearity": [[13, "example-11-encouraging-linearity"]], "Case 1: 1D function": [[13, "case-1-1d-function"]], "Case 2: 2D function": [[13, "case-2-2d-function"]], "Example 12: Unsupervised learning": [[14, "example-12-unsupervised-learning"]], "Example 13: Phase transition": [[15, "example-13-phase-transition"]], "Example 1: Function Fitting": [[16, "example-1-function-fitting"]], "Example 2: Deep Formulas": [[17, "example-2-deep-formulas"]], "Three-layer KAN": [[17, "three-layer-kan"]], "Two-layer KAN": [[17, "two-layer-kan"]], "Example 3: Classification": [[18, "example-3-classification"]], "Regression formulation": [[18, "regression-formulation"]], "Classification formulation": [[18, "classification-formulation"]], "Train KAN": [[18, "train-kan"]], "Example 4: Symbolic Regression": [[19, "example-4-symbolic-regression"]], "Part I: Automated vs manual symbolic regression (How can we know that we get the exact formula?)": [[19, "part-i-automated-vs-manual-symbolic-regression-how-can-we-know-that-we-get-the-exact-formula"]], "Part II: How hard (ill-defined) is symbolic regression, really?": [[19, "part-ii-how-hard-ill-defined-is-symbolic-regression-really"]], "1D example: Adding noise to a bounded region sine": [[19, "d-example-adding-noise-to-a-bounded-region-sine"]], "Phase diagram of symbolic regression (how fratcal/chaotic is my phase diagram?)": [[19, "phase-diagram-of-symbolic-regression-how-fratcal-chaotic-is-my-phase-diagram"]], "mix three functions f_1(x)={\\rm sin}(x), f_2(x)=x^2, and f_3(x)={\\rm exp}(x) such that f(x)=af_1(x)+bf_2(x)+(1-a-b)f_3(x). 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"indexing-of-layers"]], "Demo 2: Plotting": [[4, "demo-2-plotting"]], "Demo 3: Grid": [[5, "demo-3-grid"]], "Demo 4: Extracting activation functions": [[6, "demo-4-extracting-activation-functions"]], "Demo 5: Initialization Hyperparamters": [[7, "demo-5-initialization-hyperparamters"]], "Demo 6: Training Hyperparamters": [[8, "demo-6-training-hyperparamters"]], "Parameter 1: \\lambda, overall penalty strength.": [[8, "parameter-1-lambda-overall-penalty-strength"]], "Parameter 2: (relative) penalty strength of entropy \\lambda_{\\rm ent}.": [[8, "parameter-2-relative-penalty-strength-of-entropy-lambda-rm-ent"]], "Parameter 3: Grid size G.": [[8, "parameter-3-grid-size-g"]], "Parameter 4: seed.": [[8, "parameter-4-seed"]], "Demo 7: Pruning": [[9, "demo-7-pruning"]], "Automatic pruning": [[9, "automatic-pruning"]], "Manual pruning": [[9, "manual-pruning"]], "Demo 8: Checkpoint": [[10, "demo-8-checkpoint"]], "Demo 9: Videos": [[11, "demo-9-videos"]], "Example 10: Use of lock for Relativity Addition": [[12, "example-10-use-of-lock-for-relativity-addition"]], "Example 11: Encouraging linearity": [[13, "example-11-encouraging-linearity"]], "Case 1: 1D function": [[13, "case-1-1d-function"]], "Case 2: 2D function": [[13, "case-2-2d-function"]], "Example 12: Unsupervised learning": [[14, "example-12-unsupervised-learning"]], "Example 13: Phase transition": [[15, "example-13-phase-transition"]], "Example 1: Function Fitting": [[16, "example-1-function-fitting"]], "Example 2: Deep Formulas": [[17, "example-2-deep-formulas"]], "Three-layer KAN": [[17, "three-layer-kan"]], "Two-layer KAN": [[17, "two-layer-kan"]], "Example 3: Classification": [[18, "example-3-classification"]], "Regression formulation": [[18, "regression-formulation"]], "Classification formulation": [[18, "classification-formulation"]], "Train KAN": [[18, "train-kan"]], "Example 4: Symbolic Regression": [[19, "example-4-symbolic-regression"]], "Part I: Automated vs manual symbolic regression (How can we know that we get the exact formula?)": [[19, "part-i-automated-vs-manual-symbolic-regression-how-can-we-know-that-we-get-the-exact-formula"]], "Part II: How hard (ill-defined) is symbolic regression, really?": [[19, "part-ii-how-hard-ill-defined-is-symbolic-regression-really"]], "1D example: Adding noise to a bounded region sine": [[19, "d-example-adding-noise-to-a-bounded-region-sine"]], "Phase diagram of symbolic regression (how fratcal/chaotic is my phase diagram?)": [[19, "phase-diagram-of-symbolic-regression-how-fratcal-chaotic-is-my-phase-diagram"]], "mix three functions f_1(x)={\\rm sin}(x), f_2(x)=x^2, and f_3(x)={\\rm exp}(x) such that f(x)=af_1(x)+bf_2(x)+(1-a-b)f_3(x). Symbolically regress f(x).": [[19, "mix-three-functions-f-1-x-rm-sin-x-f-2-x-x-2-and-f-3-x-rm-exp-x-such-that-f-x-af-1-x-bf-2-x-1-a-b-f-3-x-symbolically-regress-f-x"]], "Example 5: Special functions": [[20, "example-5-special-functions"]], "Example 6: Solving Partial Differential Equation (PDE)": [[21, "example-6-solving-partial-differential-equation-pde"]], "Example 7: Continual Learning": [[22, "example-7-continual-learning"]], "Example 8: KANs\u2019 Scaling Laws": [[23, "example-8-kans-scaling-laws"]], "Example 9: Singularity": [[24, "example-9-singularity"]], "API Demos": [[25, "api-demos"], [0, "api-demos"]], "Examples": [[26, "examples"]], "Welcome to Kolmogorov Aarnold Network (KAN) documentation!": [[27, "welcome-to-kolmogorov-aarnold-network-kan-documentation"], [1, "welcome-to-kolmogorov-aarnold-network-kan-documentation"]], "Installation": [[27, "installation"]], "Installation via github": [[27, "installation-via-github"]], "Installation via PyPI": [[27, "installation-via-pypi"]], "Requirements": [[27, "requirements"]], "Get started": [[27, "get-started"]], "Contents:": [[27, null]], "Indices and tables": [[27, "indices-and-tables"], [1, "indices-and-tables"]], "Hello, KAN!": [[28, "hello-kan"]], "Kolmogorov-Arnold representation theorem": [[28, "kolmogorov-arnold-representation-theorem"]], "Kolmogorov-Arnold Network (KAN)": [[28, "kolmogorov-arnold-network-kan"]], "Get started with KANs": [[28, "get-started-with-kans"]], "API": [[30, "api"]], "kan package": [[29, "kan-package"]], "Submodules": [[29, "submodules"]], "kan.KAN module": [[29, "kan-kan-module"]], "kan.KANLayer module": [[29, "kan-kanlayer-module"]], "kan.LBFGS module": [[29, "kan-lbfgs-module"]], "kan.Symbolic_KANLayer module": [[29, "kan-symbolic-kanlayer-module"]], "kan.spline module": [[29, "kan-spline-module"]], "kan.utils module": [[29, "kan-utils-module"]], "Module contents": [[29, "module-contents"]]}, "indexentries": {}}) \ No newline at end of file