Tommi Jaakkola

Publications by Year

Research Areas

Computational Drug Discovery Methods, Machine Learning in Materials Science, Topic Modeling, Machine Learning and Algorithms, Bayesian Modeling and Causal Inference

Most-Cited Works

• → An Introduction to Variational Methods for Graphical Models(1999)3,730 cited
• → A Deep Learning Approach to Antibiotic Discovery(2020)2,067 cited
• → De novo design of protein structure and function with RFdiffusion(2023)1,692 cited
• → Analyzing Learned Molecular Representations for Property Prediction(2019)1,673 cited
• Exploiting Generative Models in Discriminative Classifiers(1998)
• Maximum-Margin Matrix Factorization(2004)
• → Prediction of Organic Reaction Outcomes Using Machine Learning(2017)799 cited
• → On the Convergence of Stochastic Iterative Dynamic Programming Algorithms(1994)796 cited
• → Junction Tree Variational Autoencoder for Molecular Graph Generation(2018)711 cited
• Weighted low-rank approximations(2003)