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Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem



Brian L. Trippe , Jason Yim , Doug Tischer , Tamara Broderick , David Baker , Regina Barzilay , Tommi Jaakkola


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Torsional Diffusion for Molecular Conformer Generation



Bowen Jing , Gabriele Corso , Jeffrey Chang , Regina Barzilay , Tommi Jaakkola


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Subspace Diffusion Generative Models



Bowen Jing , Gabriele Corso , Renato Berlinghieri , Tommi Jaakkola


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Simulate Time-integrated Coarse-grained Molecular Dynamics with Geometric Machine Learning



Xiang Fu , Tian Xie , Nathan J. Rebello , Bradley D. Olsen , Tommi Jaakkola

* 23 pages, 10 figures 

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Conformal Prediction Sets with Limited False Positives



Adam Fisch , Tal Schuster , Tommi Jaakkola , Regina Barzilay


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EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction



Hannes Stärk , Octavian-Eugen Ganea , Lagnajit Pattanaik , Regina Barzilay , Tommi Jaakkola

* Under review. 18 pages, 15 figures 

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Controlling Directions Orthogonal to a Classifier



Yilun Xu , Hao He , Tianxiao Shen , Tommi Jaakkola

* accepted by ICLR 2022 

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Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking



Octavian-Eugen Ganea , Xinyuan Huang , Charlotte Bunne , Yatao Bian , Regina Barzilay , Tommi Jaakkola , Andreas Krause


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Fragment-based Sequential Translation for Molecular Optimization



Benson Chen , Xiang Fu , Regina Barzilay , Tommi Jaakkola


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Learning Representations that Support Robust Transfer of Predictors



Yilun Xu , Tommi Jaakkola


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