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09.12.2025: Advances in Hierarchical Molecular Representations, Diffusion Models, and Self-Supervised Learning for Structural Prediction
This podcast is brought to you by the Oliver Laboratory at Vanderbilt University.
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0:00 Chemistry Integrated Language Model using Hierarchical Molecular Representation for Polymer Informatics (https://arxiv.org/pdf/2512.06301.pdf)
4:29 Hierarchical geometric deep learning enables scalable analysis of molecular dynamics (https://arxiv.org/pdf/2512.06520.pdf)
9:35 On fine-tuning Boltz-2 for protein-protein affinity prediction (https://arxiv.org/pdf/2512.06592.pdf)
14:33 Multi-Scale Protein Structure Modelling with Geometric Graph U-Nets (https://arxiv.org/pdf/2512.06752.pdf)
18:33 Self-Supervised Learning on Molecular Graphs: A Systematic Investigation of Masking Design (https://arxiv.org/pdf/2512.07064.pdf)
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Source code: https://github.com/OliverLaboratory/arxivreader
Contact: oliverlaboratory.com
Source code: https://github.com/OliverLaboratory/arxivreader
View all episodes
By This podcast is brought to you by the Oliver Laboratory at Vanderbilt University.
----------------------------------------
0:00 Chemistry Integrated Language Model using Hierarchical Molecular Representation for Polymer Informatics (https://arxiv.org/pdf/2512.06301.pdf)
4:29 Hierarchical geometric deep learning enables scalable analysis of molecular dynamics (https://arxiv.org/pdf/2512.06520.pdf)
9:35 On fine-tuning Boltz-2 for protein-protein affinity prediction (https://arxiv.org/pdf/2512.06592.pdf)
14:33 Multi-Scale Protein Structure Modelling with Geometric Graph U-Nets (https://arxiv.org/pdf/2512.06752.pdf)
18:33 Self-Supervised Learning on Molecular Graphs: A Systematic Investigation of Masking Design (https://arxiv.org/pdf/2512.07064.pdf)
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Source code: https://github.com/OliverLaboratory/arxivreader
Contact: oliverlaboratory.com
Source code: https://github.com/OliverLaboratory/arxivreader