Tommi S. Jaakkola

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 207

Top Venues

CoRR

ICML

ICLR

NeurIPS

Publications

Andrew Kirjner, Jason Yim, Raman Samusevich, Shahar Bracha, Tommi S. Jaakkola, Regina Barzilay, Ila R. Fiete
Improving protein optimization with smoothed fitness landscapes. ICLR (2024)
Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. Jaakkola
Removing Biases from Molecular Representations via Information Maximization. ICLR (2024)
Jason Yim, Andrew Campbell, Emile Mathieu, Andrew Y. K. Foong, Michael Gastegger, José Jiménez-Luna, Sarah Lewis, Victor Garcia Satorras, Bastiaan S. Veeling, Frank Noé, Regina Barzilay, Tommi S. Jaakkola
Improved motif-scaffolding with SE(3) flow matching. Trans. Mach. Learn. Res. 2024 (2024)
Gabriele Corso, Arthur Deng, Nicholas Polizzi, Regina Barzilay, Tommi S. Jaakkola
Deep Confident Steps to New Pockets: Strategies for Docking Generalization. ICLR (2024)
Bowen Jing, Bonnie Berger, Tommi S. Jaakkola
AlphaFold Meets Flow Matching for Generating Protein Ensembles. CoRR (2024)
Sharut Gupta, Chenyu Wang, Yifei Wang, Tommi S. Jaakkola, Stefanie Jegelka
In-Context Symmetries: Self-Supervised Learning through Contextual World Models. CoRR (2024)
Ryotaro Okabe, Mouyang Cheng, Abhijatmedhi Chotrattanapituk, Nguyen Tuan Hung, Xiang Fu, Bowen Han, Yao Wang, Weiwei Xie, Robert J. Cava, Tommi S. Jaakkola, Yongqiang Cheng, Mingda Li
Structural Constraint Integration in Generative Model for Discovery of Quantum Material Candidates. CoRR (2024)
Jason Yim, Andrew Campbell, Emile Mathieu, Andrew Y. K. Foong, Michael Gastegger, José Jiménez-Luna, Sarah Lewis, Victor Garcia Satorras, Bastiaan S. Veeling, Frank Noé, Regina Barzilay, Tommi S. Jaakkola
Improved motif-scaffolding with SE(3) flow matching. CoRR (2024)
Xiang Fu, Andrew S. Rosen, Kyle Bystrom, Rui Wang, Albert Musaelian, Boris Kozinsky, Tess E. Smidt, Tommi S. Jaakkola
A Recipe for Charge Density Prediction. CoRR (2024)
Victor Quach, Adam Fisch, Tal Schuster, Adam Yala, Jae Ho Sohn, Tommi S. Jaakkola, Regina Barzilay
Conformal Language Modeling. ICLR (2024)
Menghua Wu, Yujia Bao, Regina Barzilay, Tommi S. Jaakkola
Sample, estimate, aggregate: A recipe for causal discovery foundation models. CoRR (2024)
Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. CoRR (2024)
Yujian Liu, Yang Zhang, Tommi S. Jaakkola, Shiyu Chang
Revisiting Who's Harry Potter: Towards Targeted Unlearning from a Causal Intervention Perspective. CoRR (2024)
Bowen Jing, Tommi S. Jaakkola, Bonnie Berger
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms. ICLR (2024)
Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models. ICLR (2024)
Gabriele Corso, Arthur Deng, Benjamin Fry, Nicholas Polizzi, Regina Barzilay, Tommi S. Jaakkola
Deep Confident Steps to New Pockets: Strategies for Docking Generalization. CoRR (2024)
Ezra Erives, Bowen Jing, Tommi S. Jaakkola
Verlet Flows: Exact-Likelihood Integrators for Flow-Based Generative Models. CoRR (2024)
Andrew Campbell, Jason Yim, Regina Barzilay, Tom Rainforth, Tommi S. Jaakkola
Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design. CoRR (2024)
Hannes Stärk, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, Tommi S. Jaakkola
Dirichlet Flow Matching with Applications to DNA Sequence Design. CoRR (2024)
Xiang Fu, Tian Xie, Andrew S. Rosen, Tommi S. Jaakkola, Jake Smith
MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design. ICLR (2024)
Ryotaro Okabe, Abhijatmedhi Chotrattanapituk, Artittaya Boonkird, Nina Andrejevic, Xiang Fu, Tommi S. Jaakkola, Qichen Song, Thanh Nguyen, Nathan C. Drucker, Sai Mu, Yao Wang, Bolin Liao, Yongqiang Cheng, Mingda Li
Virtual node graph neural network for full phonon prediction. Nat. Comput. Sci. 4 (7) (2024)
Bracha Laufer-Goldshtein, Adam Fisch, Regina Barzilay, Tommi S. Jaakkola
Risk-Controlling Model Selection via Guided Bayesian Optimization. CoRR (2023)
Yilun Xu, Shangyuan Tong, Tommi S. Jaakkola
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models. ICLR (2023)
Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi S. Jaakkola
Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem. ICLR (2023)
Andrew Kirjner, Jason Yim, Raman Samusevich, Tommi S. Jaakkola, Regina Barzilay, Ila Fiete
Optimizing protein fitness using Gibbs sampling with Graph-based Smoothing. CoRR (2023)
Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, Pulkit Agrawal
Is Conditional Generative Modeling all you need for Decision Making? ICLR (2023)
Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas K. Garg, Samuel Kaski, Tommi S. Jaakkola
Compositional Sculpting of Iterative Generative Processes. NeurIPS (2023)
Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. CoRR (2023)
Yilun Xu, Shangyuan Tong, Tommi S. Jaakkola
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models. CoRR (2023)
Bowen Jing, Ezra Erives, Peter Pao-Huang, Gabriele Corso, Bonnie Berger, Tommi S. Jaakkola
EigenFold: Generative Protein Structure Prediction with Diffusion Models. CoRR (2023)
Yujian Liu, Yang Zhang, Tommi S. Jaakkola, Shiyu Chang
Correcting Diffusion Generation through Resampling. CoRR (2023)
Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. Jaakkola
Removing Biases from Molecular Representations via Information Maximization. CoRR (2023)
Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR (2023)
Guanhua Zhang, Jiabao Ji, Yang Zhang, Mo Yu, Tommi S. Jaakkola, Shiyu Chang
Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models. ICML (2023)
Xiang Fu, Zhenghao Wu, Wujie Wang, Tian Xie, Sinan Keten, Rafael Gómez-Bombarelli, Tommi S. Jaakkola
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations. Trans. Mach. Learn. Res. 2023 (2023)
Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola
SE(3) diffusion model with application to protein backbone generation. ICML (2023)
Xiang Fu, Tian Xie, Nathan J. Rebello, Bradley D. Olsen, Tommi S. Jaakkola
Simulate Time-integrated Coarse-grained Molecular Dynamics with Multi-scale Graph Networks. Trans. Mach. Learn. Res. 2023 (2023)
Guanhua Zhang, Jiabao Ji, Yang Zhang, Mo Yu, Tommi S. Jaakkola, Shiyu Chang
Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models. CoRR (2023)
Bowen Jing, Tommi S. Jaakkola, Bonnie Berger
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms. CoRR (2023)
Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas K. Garg, Samuel Kaski, Tommi S. Jaakkola
Compositional Sculpting of Iterative Generative Processes. CoRR (2023)
Victor Quach, Adam Fisch, Tal Schuster, Adam Yala, Jae Ho Sohn, Tommi S. Jaakkola, Regina Barzilay
Conformal Language Modeling. CoRR (2023)
Ziming Liu, Di Luo, Yilun Xu, Tommi S. Jaakkola, Max Tegmark
GenPhys: From Physical Processes to Generative Models. CoRR (2023)
Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi S. Jaakkola, Josh Tenenbaum, Leslie Pack Kaelbling, Akash Srivastava, Pulkit Agrawal
Compositional Foundation Models for Hierarchical Planning. CoRR (2023)
Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola
Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design. CoRR (2023)
Mohamed Amine Ketata, Cedrik Laue, Ruslan Mammadov, Hannes Stärk, Menghua Wu, Gabriele Corso, Céline Marquet, Regina Barzilay, Tommi S. Jaakkola
DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models. CoRR (2023)
Bracha Laufer-Goldshtein, Adam Fisch, Regina Barzilay, Tommi S. Jaakkola
Efficiently Controlling Multiple Risks with Pareto Testing. ICLR (2023)
Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking. ICLR (2023)
Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi S. Jaakkola
Restart Sampling for Improving Generative Processes. NeurIPS (2023)
Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi S. Jaakkola
Restart Sampling for Improving Generative Processes. CoRR (2023)
Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models. CoRR (2023)
Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola
SE(3) diffusion model with application to protein backbone generation. CoRR (2023)
Xiang Fu, Tian Xie, Andrew S. Rosen, Tommi S. Jaakkola, Jake Smith
MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design. CoRR (2023)
Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. ICML (2023)
Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi S. Jaakkola, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Akash Srivastava, Pulkit Agrawal
Compositional Foundation Models for Hierarchical Planning. NeurIPS (2023)
Homa Esfahanizadeh, Adam Yala, Rafael G. L. D'Oliveira, Andrea J. D. Jaba, Victor Quach, Ken R. Duffy, Tommi S. Jaakkola, Vinod Vaikuntanathan, Manya Ghobadi, Regina Barzilay, Muriel Médard
PEOPL: Characterizing Privately Encoded Open Datasets with Public Labels. CoRR (2023)
Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola
Poisson Flow Generative Models. NeurIPS (2022)
Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi S. Jaakkola
Subspace Diffusion Generative Models. CoRR (2022)
Shangyuan Tong, Timur Garipov, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola
Adversarial Support Alignment. ICLR (2022)
Yilun Xu, Hao He, Tianxiao Shen, Tommi S. Jaakkola
Controlling Directions Orthogonal to a Classifier. ICLR (2022)
Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design. ICLR (2022)
Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking. ICLR (2022)
Xiang Fu, Tian Xie, Nathan J. Rebello, Bradley D. Olsen, Tommi S. Jaakkola
Simulate Time-integrated Coarse-grained Molecular Dynamics with Geometric Machine Learning. CoRR (2022)
Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar
Fundamental Limits and Tradeoffs in Invariant Representation Learning. J. Mach. Learn. Res. 23 (2022)
Shangyuan Tong, Timur Garipov, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola
Adversarial Support Alignment. CoRR (2022)
Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, Pulkit Agrawal
Is Conditional Generative Modeling all you need for Decision-Making? CoRR (2022)
Adam Yala, Victor Quach, Homa Esfahanizadeh, Rafael G. L. D'Oliveira, Ken R. Duffy, Muriel Médard, Tommi S. Jaakkola, Regina Barzilay
Syfer: Neural Obfuscation for Private Data Release. CoRR (2022)
Xiang Fu, Zhenghao Wu, Wujie Wang, Tian Xie, Sinan Keten, Rafael Gómez-Bombarelli, Tommi S. Jaakkola
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations. CoRR (2022)
Adam Fisch, Tommi S. Jaakkola, Regina Barzilay
Calibrated Selective Classification. Trans. Mach. Learn. Res. 2022 (2022)
Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, Tommi S. Jaakkola
Torsional Diffusion for Molecular Conformer Generation. NeurIPS (2022)
Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, Tommi S. Jaakkola
Torsional Diffusion for Molecular Conformer Generation. CoRR (2022)
Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola
Poisson Flow Generative Models. CoRR (2022)
Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi S. Jaakkola
Crystal Diffusion Variational Autoencoder for Periodic Material Generation. ICLR (2022)
Tal Schuster, Adam Fisch, Tommi S. Jaakkola, Regina Barzilay
Consistent Accelerated Inference via Confident Adaptive Transformers. EMNLP (1) (2021)
Tal Schuster, Adam Fisch, Tommi S. Jaakkola, Regina Barzilay
Consistent Accelerated Inference via Confident Adaptive Transformers. CoRR (2021)
Octavian-Eugen Ganea, Lagnajit Pattanaik, Connor W. Coley, Regina Barzilay, Klavs F. Jensen, William H. Green Jr., Tommi S. Jaakkola
GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles. CoRR (2021)
Mo Yu, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola
Understanding Interlocking Dynamics of Cooperative Rationalization. NeurIPS (2021)
Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design. CoRR (2021)
Adam Yala, Homa Esfahanizadeh, Rafael G. L. D'Oliveira, Ken R. Duffy, Manya Ghobadi, Tommi S. Jaakkola, Vinod Vaikuntanathan, Regina Barzilay, Muriel Médard
NeuraCrypt: Hiding Private Health Data via Random Neural Networks for Public Training. CoRR (2021)
Wengong Jin, Jonathan M. Stokes, Richard T. Eastman, Zina Itkin, Alexey V. Zakharov, James J. Collins, Tommi S. Jaakkola, Regina Barzilay
Deep learning identifies synergistic drug combinations for treating COVID-19. Proc. Natl. Acad. Sci. USA 118 (39) (2021)
Adam Fisch, Tal Schuster, Tommi S. Jaakkola, Regina Barzilay
Efficient Conformal Prediction via Cascaded Inference with Expanded Admission. ICLR (2021)
Adam Fisch, Tal Schuster, Tommi S. Jaakkola, Regina Barzilay
Few-shot Conformal Prediction with Auxiliary Tasks. CoRR (2021)
Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi S. Jaakkola
Learning Task Informed Abstractions. CoRR (2021)
Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi S. Jaakkola
Crystal Diffusion Variational Autoencoder for Periodic Material Generation. CoRR (2021)
Octavian Ganea, Lagnajit Pattanaik, Connor W. Coley, Regina Barzilay, Klavs F. Jensen, William H. Green Jr., Tommi S. Jaakkola
GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles. NeurIPS (2021)
Mo Yu, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola
Understanding Interlocking Dynamics of Cooperative Rationalization. CoRR (2021)
Karren D. Yang, Samuel Goldman, Wengong Jin, Alex X. Lu, Regina Barzilay, Tommi S. Jaakkola, Caroline Uhler
Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis. CVPR (2021)
Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi S. Jaakkola
Learning Task Informed Abstractions. ICML (2021)
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov
Information Obfuscation of Graph Neural Networks. ICML (2021)
Benson Chen, Xiang Fu, Regina Barzilay, Tommi S. Jaakkola
Fragment-based Sequential Translation for Molecular Optimization. CoRR (2021)
Adam Fisch, Tal Schuster, Tommi S. Jaakkola, Regina Barzilay
Few-Shot Conformal Prediction with Auxiliary Tasks. ICML (2021)
Shiyu Chang, Yang Zhang, Mo Yu, Tommi S. Jaakkola
Invariant Rationalization. ICML (2020)
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov
Graph Adversarial Networks: Protecting Information against Adversarial Attacks. CoRR (2020)
Vikas K. Garg, Stefanie Jegelka, Tommi S. Jaakkola
Generalization and Representational Limits of Graph Neural Networks. CoRR (2020)
Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar
Fundamental Limits and Tradeoffs in Invariant Representation Learning. CoRR (2020)
Karren D. Yang, Samuel Goldman, Wengong Jin, Alex Lu, Regina Barzilay, Tommi S. Jaakkola, Caroline Uhler
Improved Conditional Flow Models for Molecule to Image Synthesis. CoRR (2020)
Tianxiao Shen, Jonas Mueller, Regina Barzilay, Tommi S. Jaakkola
Educating Text Autoencoders: Latent Representation Guidance via Denoising. ICML (2020)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Multi-Objective Molecule Generation using Interpretable Substructures. ICML (2020)
Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi S. Jaakkola
Improving Molecular Design by Stochastic Iterative Target Augmentation. CoRR (2020)
Shangyuan Tong, Timur Garipov, Tommi S. Jaakkola
The Benefits of Pairwise Discriminators for Adversarial Training. CoRR (2020)
Chen-Yu Hsu, Abbas Zeitoun, Guang-He Lee, Dina Katabi, Tommi S. Jaakkola
Self-Supervised Learning of Appliance Usage. ICLR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Tommi S. Jaakkola