Stephan Eismann

Publication Activity (10 Years)

Years Active: 2015-2021
Publications (10 Years): 13

Top Topics

Protein Complexes

Structure Learning

Computational Approaches

Top Venues

NeurIPS Datasets and Benchmarks

Publications

Raphael J. L. Townshend, Martin Vögele, Patricia Suriana, Alexander Derry, Alexander Powers, Yianni Laloudakis, Sidhika Balachandar, Bowen Jing, Brandon M. Anderson, Stephan Eismann, Risi Kondor, Russ B. Altman, Ron O. Dror
ATOM3D: Tasks on Molecules in Three Dimensions. NeurIPS Datasets and Benchmarks (2021)
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael John Lamarre Townshend, Ron O. Dror
Learning from Protein Structure with Geometric Vector Perceptrons. ICLR (2021)
Bowen Jing, Stephan Eismann, Pratham N. Soni, Ron O. Dror
Equivariant Graph Neural Networks for 3D Macromolecular Structure. CoRR (2021)
Elodie Laine, Stephan Eismann, Arne Elofsson, Sergei Grudinin
Protein sequence-to-structure learning: Is this the end(-to-end revolution)? CoRR (2021)
Raphael J. L. Townshend, Brent Townshend, Stephan Eismann, Ron O. Dror
Geometric Prediction: Moving Beyond Scalars. CoRR (2020)
Stephan Eismann, Raphael J. L. Townshend, Nathaniel Thomas, Milind Jagota, Bowen Jing, Ron O. Dror
Hierarchical, rotation-equivariant neural networks to predict the structure of protein complexes. CoRR (2020)
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J. L. Townshend, Ron O. Dror
Learning from Protein Structure with Geometric Vector Perceptrons. CoRR (2020)
Stephan Eismann, Patricia Suriana, Bowen Jing, Raphael J. L. Townshend, Ron O. Dror
Protein model quality assessment using rotation-equivariant, hierarchical neural networks. CoRR (2020)
Raphael J. L. Townshend, Martin Vögele, Patricia Suriana, Alexander Derry, Alexander Powers, Yianni Laloudakis, Sidhika Balachandar, Brandon M. Anderson, Stephan Eismann, Risi Kondor, Russ B. Altman, Ron O. Dror
ATOM3D: Tasks On Molecules in Three Dimensions. CoRR (2020)
Jun-Ting Hsieh, Shengjia Zhao, Stephan Eismann, Lucia Mirabella, Stefano Ermon
Learning Neural PDE Solvers with Convergence Guarantees. ICLR (Poster) (2019)
Jun-Ting Hsieh, Shengjia Zhao, Stephan Eismann, Lucia Mirabella, Stefano Ermon
Learning Neural PDE Solvers with Convergence Guarantees. CoRR (2019)
Stephan Eismann, Daniel Levy, Rui Shu, Stefan Bartzsch, Stefano Ermon
Bayesian optimization and attribute adjustment. UAI (2018)
Stephan Eismann, Stefan Bartzsch, Stefano Ermon
Shape optimization in laminar flow with a label-guided variational autoencoder. CoRR (2017)
Stephan Eismann, Robert G. Endres
Protein Connectivity in Chemotaxis Receptor Complexes. PLoS Comput. Biol. 11 (12) (2015)