{"id":21409273,"url":"https://github.com/acerbilab/amortized-conditioning-engine","last_synced_at":"2026-03-07T18:01:19.933Z","repository":{"id":258963330,"uuid":"874874734","full_name":"acerbilab/amortized-conditioning-engine","owner":"acerbilab","description":"Amortized Probabilistic Conditioning for Optimization, Simulation and Inference (Chang et al., AISTATS 2025)","archived":false,"fork":false,"pushed_at":"2026-01-27T08:52:57.000Z","size":299071,"stargazers_count":21,"open_issues_count":1,"forks_count":2,"subscribers_count":3,"default_branch":"main","last_synced_at":"2026-01-27T21:05:12.694Z","etag":null,"topics":["bayesian-optimization","meta-learning","neural-processes","probabilistic-machine-learning","simulation-based-inference"],"latest_commit_sha":null,"homepage":"https://acerbilab.github.io/amortized-conditioning-engine/","language":"Jupyter 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repository will provide the implementation and code used in the AISTATS 2025 article *Amortized Probabilistic Conditioning for Optimization, Simulation and Inference* (Chang et al., 2025).\nThe full paper can be found on arXiv at: [https://arxiv.org/abs/2410.15320](https://arxiv.org/abs/2410.15320).\n\n## Installation with Anaconda\nTo install the required dependencies, run:\n\n```bash\nconda install python=3.9.19 pytorch=2.2.0 torchvision=0.17.0 torchaudio=2.2.0 -c pytorch\npip install -e .\n```\n\n## Demos\nAt the moment, we release three demo notebooks with examples of our method, the Amortized Conditioning Engine (ACE).\n\n- [`1.MNIST_demo.ipynb`](1.MNIST_demo.ipynb): Image completion demo with MNIST.\n- [`2.BO_demo.ipynb`](2.BO_demo.ipynb): Bayesian optimization demo.\n- [`3.SBI_demo.ipynb`](3.SBI_demo.ipynb): Simulation-based inference demo.\n\nEach notebook demonstrates a specific application of ACE. Simply open the notebooks in Jupyter or in GitHub to visualize the demos.\n\nFull code for this project will be made available later.\n\n## Citation\nIf you find this work valuable for your research, please consider citing our paper:\n\n```\n@article{chang2025amortized,\n  title={Amortized Probabilistic Conditioning for Optimization, Simulation and Inference},\n  author={Chang, Paul E and Loka, Nasrulloh and Huang, Daolang and Remes, Ulpu and Kaski, Samuel and Acerbi, Luigi},\n  journal={28th Int. Conf. on Artificial Intelligence \u0026 Statistics (AISTATS 2025)},\n  year={2025}\n}\n```\n\n## License\nThis code is released under the Apache 2.0 License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Facerbilab%2Famortized-conditioning-engine","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Facerbilab%2Famortized-conditioning-engine","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Facerbilab%2Famortized-conditioning-engine/lists"}