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.github/workflows/bib2readme.py

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This is a curated list of resources, including reviews, software, papers, and other resources related to amortized inference.
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Feel free to explore the entries below and use the provided BibTeX information for citation purposes.
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This is a community-driven project which is currently maintained by [Marvin Schmitt](https://www.marvinschmitt.com).
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Contributions are always welcome, see [`CONTRIBUTING.md`](https://github.com/bayesflow-org/awesome-amortized-inference/blob/main/CONTRIBUTING.md) for a contribution guide.
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Contributions are always welcome, see [`CONTRIBUTING.md`](https://github.com/bayesflow-org/awesome-amortized-inference/blob/main/CONTRIBUTING.md) for a contribution guide 🧡
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This awesome list currently has some overlap with the `awesome-neural-sbi` list ([Link](https://github.com/smsharma/awesome-neural-sbi)) because
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This list currently has some overlap with the `awesome-neural-sbi` list ([Link](https://github.com/smsharma/awesome-neural-sbi)) because
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amortized inference has gained populatity in the context of simulation-based inference (SBI) with neural networks.
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However, there is a trend towards broader amortized inference methods that are not necessarily simulation-based.
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This list aims to cover all amortized inference methods, including but not limited to simulation-based inference.
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We highly recommend checking out the `awesome-neural-sbi` list for more resources on modern simulation-based inference with neural networks.
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We highly recommend checking out these lists for more resources on modern simulation-based inference:
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- [awesome-neural-sbi](https://github.com/smsharma/awesome-neural-sbi)
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- [simulation-based inference website](https://simulation-based-inference.org/)
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- [Introduction to simulation-based inference by TransferLab](https://transferlab.ai/trainings/simulation-based-inference/)
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> 🚧 **Under construction** 🚧
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> This repository is a development version under construction. The list of resources is just a small set for debugging and development purposes.
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> For now, we focus on developing features that we think could be useful for the community (e.g., `BibTeX`-first structure).
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> Then, we will evaluate whether this project has the potential to be useful for the community in addition to existing lists
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> that are specifically designated to *simulation-based inference* and not *amortized inference* (which doesn't need to be simulation-based).
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> Once we figure out the direction and deem the project potentially useful for the community, we'll launch and add an extensive set of resources
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> -- hopefully with the help of many awesome people from the community 🧡
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"""
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