1999
An Introduction to Variational Methods for Graphical Models
Michael I. Jordan, Zoubin Ghahramani, Tommi Jaakkola, Lawrence K. Saul
Machine Learning OATop-listed
3.8k
cites
Tommi Jaakkola
Researcher
Computational Drug Discovery MethodsMachine Learning and AlgorithmsTopic Modeling
About
Tommi Jaakkola is a Computer Science scholar at IIT@MIT. Research spans Computational Drug Discovery Methods, Machine Learning and Algorithms, Topic Modeling. 424 works, 47k citations (h-index 91).
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Affiliation on publications · IIT@MIT
Most-cited work
2020
A Deep Learning Approach to Antibiotic Discovery
Jonathan M. Stokes, Kevin Yang, Kyle Swanson, Wengong Jin, Andrés Cubillos-Ruiz, Nina M. Donghia, Craig R. MacNair, Shawn French, Lindsey A. Carfrae, Zohar Bloom‐Ackermann, Victoria M. Tran, Anush Chiappino-Pepe, Ahmed H. Badran, Ian W. Andrews, Emma J. Chory, George McDonald Church, Eric D. Brown, Tommi Jaakkola, Regina Barzilay, James J. Collins
Cell OATop-listed
2.4k
cites
2023
De novo design of protein structure and function with RFdiffusion
Joseph L. Watson, David Juergens, Nathaniel R. Bennett, Brian Loeber Trippe, Jason Yim, Helen E. Eisenach, Woody Ahern, Andrew J. Borst, Robert J. Ragotte, Lukas F. Milles, Basile I. M. Wicky, Nikita Hanikel, Samuel J. Pellock, Alexis Courbet, William Sheffler, Jue Wang, Preetham Venkatesh, Isaac Sappington, Susana Vázquez Torres, Anna Lauko, Valentin De Bortoli, Émile Mathieu, Sergey Ovchinnikov, Regina Barzilay, Tommi Jaakkola, Frank DiMaio, Minkyung Baek, David A. Baker
Nature OATop-listed
2.3k
cites