{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-bayesian-flow-network-framework-for","title":"A Bayesian Flow Network Framework for Chemistry Tasks","arxiv_id":"2407.20294","date":"2024-07-28","proceeding":null,"authors":["Nianze Tao","Minori Abe"],"abstract":"In this work, we introduce ChemBFN, a language model that handles chemistry tasks based on Bayesian flow networks working on discrete data. A new accuracy schedule is proposed to improve the sampling quality by significantly reducing the reconstruction loss. We show evidence that our method is appropriate for generating molecules with satisfied diversity even when a smaller number of sampling steps is used. A classifier-free guidance method is adapted for conditional generation. It is also worthwhile to point out that after generative training, our model can be fine-tuned on regression and classification tasks with the state-of-the-art performance, which opens the gate of building all-in-one models in a single module style. Our model has been open sourced at https://github.com/Augus1999/bayesian-flow-network-for-chemistry.","url_abs":"https://arxiv.org/abs/2407.20294v2","url_pdf":"https://arxiv.org/pdf/2407.20294v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-bayesian-flow-network-framework-for","repo_url":"https://github.com/Augus1999/bayesian-flow-network-for-chemistry","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"diversity","task_name":"Diversity"},{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"molecular-property-prediction","task_name":"Molecular Property Prediction"},{"task_slug":"text-based-de-novo-molecule-generation","task_name":"Text-based de novo Molecule Generation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/molecular-property-prediction-on-bace-1","task":"Molecular Property Prediction","dataset":"BACE","model":"ChemBFN","rank_in_archive_order":15,"of":20,"metrics":{"ROC-AUC":"73.56"},"uses_additional_data":false},{"leaderboard":"/sota/molecular-property-prediction-on-bbbp-1","task":"Molecular Property Prediction","dataset":"BBBP","model":"ChemBFN","rank_in_archive_order":2,"of":29,"metrics":{"ROC-AUC":"95.74"},"uses_additional_data":false},{"leaderboard":"/sota/molecular-property-prediction-on-esol","task":"Molecular Property Prediction","dataset":"ESOL","model":"ChemBFN","rank_in_archive_order":17,"of":20,"metrics":{"RMSE":"0.884"},"uses_additional_data":false},{"leaderboard":"/sota/molecular-property-prediction-on-freesolv","task":"Molecular Property Prediction","dataset":"FreeSolv","model":"ChemBFN","rank_in_archive_order":11,"of":22,"metrics":{"RMSE":"1.418"},"uses_additional_data":false},{"leaderboard":"/sota/molecular-property-prediction-on-hiv-1","task":"Molecular Property Prediction","dataset":"HIV","model":"ChemBFN","rank_in_archive_order":3,"of":4,"metrics":{"ROC-AUC":"79.37"},"uses_additional_data":false},{"leaderboard":"/sota/molecular-property-prediction-on-hiv-dataset","task":"Molecular Property Prediction","dataset":"HIV dataset","model":"ChemBFN","rank_in_archive_order":3,"of":11,"metrics":{"AUC":"0.794"},"uses_additional_data":false},{"leaderboard":"/sota/molecular-property-prediction-on","task":"Molecular Property Prediction","dataset":"Lipophilicity","model":"ChemBFN","rank_in_archive_order":7,"of":13,"metrics":{"RMSE":"0.746"},"uses_additional_data":false},{"leaderboard":"/sota/molecular-property-prediction-on-clintox-1","task":"Molecular Property Prediction","dataset":"clintox","model":"ChemBFN","rank_in_archive_order":2,"of":20,"metrics":{"ROC-AUC":"99.18"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}