Jaakkola, Tommi

An Introduction to Variational Methods for Graphical Models

Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., & Saul, L. K. (1999) · Machine Learning

Bayesian Modeling and Causal InferenceGaussian Processes and Bayesian Inference

Cited by 3,791

A Deep Learning Approach to Antibiotic Discovery

Stokes, J. M., Yang, K., Swanson, K., Jin, W., Cubillos-Ruiz, A., Donghia, N. M., MacNair, C. R., French, S., Carfrae, L. A., Bloom-Ackermann, Z., et al. (2020) · Cell

Computational Drug Discovery MethodsMicrobial Natural Products and Biosynthesis

Cited by 2,463

Expanded encyclopaedias of DNA elements in the human and mouse genomes

The ENCODE Project Consortium, Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Ai, R., Aken, B., Akiyama, J. A., Jammal, O. A., et al. (2020) · Nature

Genomics and Chromatin DynamicsEpigenetics and DNA Methylation

Cited by 2,378

Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models

Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2022) · Nature

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 2,369

De novo design of protein structure and function with RFdiffusion

Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2023) · Nature

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 2,325

Analyzing Learned Molecular Representations for Property Prediction

Yang, K., Swanson, K., Jin, W., Coley, C., Eiden, P., Gao, H., Guzman-Perez, A., Hopper, T., Kelley, B., Mathea, M., et al. (2019) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 1,923

Rationalizing Neural Predictions

Lei, T., Barzilay, R., & Jaakkola, T. (2016) · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

Explainable Artificial Intelligence (XAI)Sentiment Analysis and Opinion Mining

Cited by 777

A graph-convolutional neural network model for the prediction of chemical reactivity

Coley, C. W., Jin, W., Rogers, L., Jamison, T. F., Jaakkola, T. S., Green, W. H., Barzilay, R., & Jensen, K. F. (2019) · Chemical Science

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 679

Convolutional embedding of attributed molecular graphs for physical property prediction

Coley, C. W., Barzilay, R., Green, W. H., Jaakkola, T. S., & Jensen, K. F. (2017) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsGraph theory and applications

Cited by 470

On the Robustness of Interpretability Methods

Alvarez-Melis, D., & Jaakkola, T. S. (2018) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 310

Benchmarking AlphaFold‐enabled molecular docking predictions for antibiotic discovery

Wong, F., Krishnan, A., Zheng, E. J., Stärk, H., Manson, A. L., Earl, A. M., Jaakkola, T., & Collins, J. J. (2022) · Molecular Systems Biology

Computational Drug Discovery MethodsProtein Structure and Dynamics

Cited by 284

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

Trippe, B. L., Yim, J., Tischer, D., Baker, D., Broderick, T., Barzilay, R., & Jaakkola, T. (2022) · arXiv

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 92

Is Conditional Generative Modeling all you need for Decision-Making?

Ajay, A., Du, Y., Gupta, A., Tenenbaum, J., Jaakkola, T., & Agrawal, P. (2022) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 61

Enforcing Predictive Invariance across Structured Biomedical Domains

Jin, W., Barzilay, R., & Jaakkola, T. (2020) · arXiv

Domain Adaptation and Few-Shot LearningComputational Drug Discovery Methods

Cited by 8

How Well Do Agentic Skills Work in the Wild: Benchmarking LLM Skill Usage in Realistic Settings

Liu, Y., Ji, J., An, L., Jaakkola, T., Zhang, Y., & Chang, S. (2026) · arXiv

Information Retrieval and Search BehaviorAI-based Problem Solving and Planning

Cited by 1