diff --git a/README.md b/README.md
index a85b4034..a820824a 100644
--- a/README.md
+++ b/README.md
@@ -1,26 +1,35 @@
-# PEtab SciML
-*A data format for scientific machine learning*
+
+
+
+
+
+
+
+
+_Data format and tooling for scientific machine learning modeling_
[](https://github.com/PEtab-dev/petab_sciml/actions/workflows/ci.yml?query=branch%3Amain)
[](https://codecov.io/gh/PEtab-dev/petab_sciml)
-[Getting Started](https://petab-sciml.readthedocs.io/latest/examples/getting_started/getting_started.html) |
-[Documentation](https://petab-sciml.readthedocs.io/latest/introduction.html) |
+[Getting Started](https://petab-sciml.readthedocs.io/latest/examples/getting_started/getting_started.html)
+| [Documentation](https://petab-sciml.readthedocs.io/latest/introduction.html) |
[Contributing](https://petab-sciml.readthedocs.io/latest/_tmp/CONTRIBUTING.html)
PEtab SciML is a table-based data format for creating training (parameter estimation)
problems for **scientific machine learning (SciML)** models that combine machine learning
and mechanistic ordinary differential equation (ODE) models.
-> [!WARNING]
-> **Beta Disclaimer**: this software is under active development and may contain bugs or instabilities. The PEtab SciML format is finalised and support for it has been implemented in PEtab importers, though not yet released. Documentation and utility functions are currently being added.
+> [!WARNING] **Beta Disclaimer**: this software is under active development and may contain
+> bugs or instabilities. The PEtab SciML format is finalised and support for it has been
+> implemented in PEtab importers, though not yet released. Documentation and utility
+> functions are currently being added.
## Major features
-Extending the [PEtab format](https://petab.readthedocs.io) for mechanistic ODE models,
-PEtab SciML provides a human readable, reproducible way to specify SciML training problems
-across diverse scenarios, in a format directly importable by downstream tools. The main
-aspects enabling this are:
+Extending the [PEtab format](https://petab.readthedocs.io) for mechanistic ODE models, PEtab
+SciML provides a human readable, reproducible way to specify SciML training problems across
+diverse scenarios, in a format directly importable by downstream tools. The main aspects
+enabling this are:
- **Flexible hybridization.** Machine learning (ML) and ODE models can be combined in three
ways: (1) ML within the ODE dynamics (includes **Neural ODEs**), (2) ML in the
@@ -30,10 +39,9 @@ aspects enabling this are:
toolboxes for dynamic-model training in Julia
([PEtab.jl](https://github.com/sebapersson/PEtab.jl)) and Python/JAX
([AMICI](https://github.com/AMICI-dev/AMICI)).
-- **Broad support for ML architectures.** A diverse set of ML architectures can be
- specified via an exchangeable PEtab SciML YAML format (supports export from PyTorch
- modules), or via importer-specific libraries (e.g., Lux.jl in PEtab.jl; Equinox in
- AMICI).
+- **Broad support for ML architectures.** A diverse set of ML architectures can be specified
+ via an exchangeable PEtab SciML YAML format (supports export from PyTorch modules), or via
+ importer-specific libraries (e.g., Lux.jl in PEtab.jl; Equinox in AMICI).
- **Diverse model types.** All model features of the
[PEtab format](https://petab.readthedocs.io) are supported, like models with partial
observability, multiple simulation conditions, diverse noise models, and/or events.
diff --git a/doc/conf.py b/doc/conf.py
index 43bdb379..993d66b5 100644
--- a/doc/conf.py
+++ b/doc/conf.py
@@ -80,6 +80,11 @@
"type": "fontawesome",
},
],
+ "logo": {
+ "image_light": "logo/logo_light.png",
+ "image_dark": "logo/logo_dark.png",
+ "alt_text": "PEtab SciML",
+ },
"navbar_center": ["navbar-nav"],
"navbar_end": ["theme-switcher", "navbar-icon-links"],
"navbar_persistent": ["search-button"],
diff --git a/doc/format_overview.rst b/doc/format_overview.rst
index bc91522b..90119c34 100644
--- a/doc/format_overview.rst
+++ b/doc/format_overview.rst
@@ -11,3 +11,4 @@ contribute to the development of PEtab SciML.
Format Specification
Supported Layers and Activation Functions
Development process
+ PEtab SciML logo license
diff --git a/doc/logo.rst b/doc/logo.rst
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+PEtab SciML logo license
+========================
+
+The PEtab SciML logo is free to use under the
+`CC0 `__ license
+and is available in both SVG and PNG formats in the
+`logo directory `__.
+Feel free to use it in any presentation or publication that uses PEtab SciML.
+
+.. container:: figure align-center
+
+ .. image:: logo/logo_light.png
+ :class: only-light
+
+ .. image:: logo/logo_dark.png
+ :class: only-dark
+
+ .. container:: caption
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