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Tommi S. Jaakkola
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- affiliation: MIT, Computer Science and Artificial Intelligence Laboratory
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2020 – today
- 2024
- [j37]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): 522-531 (2024) - [j36]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) - [c177]Yujian Liu, Yang Zhang, Tommi S. Jaakkola, Shiyu Chang:
Correcting Diffusion Generation Through Resampling. CVPR 2024: 8713-8723 - [c176]Yujian Liu, Yang Zhang, Tommi S. Jaakkola, Shiyu Chang:
Revisiting Who's Harry Potter: Towards Targeted Unlearning from a Causal Intervention Perspective. EMNLP 2024: 8708-8731 - [c175]Xiang Fu, Tian Xie, Andrew S. Rosen, Tommi S. Jaakkola, Jake Smith:
MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design. ICLR 2024 - [c174]Gabriele Corso, Arthur Deng, Nicholas Polizzi, Regina Barzilay, Tommi S. Jaakkola:
Deep Confident Steps to New Pockets: Strategies for Docking Generalization. ICLR 2024 - [c173]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 - [c172]Bowen Jing, Tommi S. Jaakkola, Bonnie Berger:
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms. ICLR 2024 - [c171]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 - [c170]Victor Quach, Adam Fisch, Tal Schuster, Adam Yala, Jae Ho Sohn, Tommi S. Jaakkola, Regina Barzilay:
Conformal Language Modeling. ICLR 2024 - [c169]Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. Jaakkola:
Removing Biases from Molecular Representations via Information Maximization. ICLR 2024 - [c168]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. ICML 2024 - [c167]Bowen Jing, Bonnie Berger, Tommi S. Jaakkola:
AlphaFold Meets Flow Matching for Generating Protein Ensembles. ICML 2024 - [c166]Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola:
Harmonic Self-Conditioned Flow Matching for joint Multi-Ligand Docking and Binding Site Design. ICML 2024 - [c165]Hannes Stärk, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, Tommi S. Jaakkola:
Dirichlet Flow Matching with Applications to DNA Sequence Design. ICML 2024 - [c164]Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis:
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. ICML 2024 - [c163]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. NeurIPS 2024 - [c162]Bowen Jing, Hannes Stärk, Tommi S. Jaakkola, Bonnie Berger:
Generative Modeling of Molecular Dynamics Trajectories. NeurIPS 2024 - [i147]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 abs/2401.04082 (2024) - [i146]Menghua Wu, Yujia Bao, Regina Barzilay, Tommi S. Jaakkola:
Sample, estimate, aggregate: A recipe for causal discovery foundation models. CoRR abs/2402.01929 (2024) - [i145]Bowen Jing, Bonnie Berger, Tommi S. Jaakkola:
AlphaFold Meets Flow Matching for Generating Protein Ensembles. CoRR abs/2402.04845 (2024) - [i144]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 abs/2402.04997 (2024) - [i143]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 abs/2402.05841 (2024) - [i142]Gabriele Corso, Arthur Deng, Benjamin Fry
, Nicholas Polizzi, Regina Barzilay, Tommi S. Jaakkola:
Deep Confident Steps to New Pockets: Strategies for Docking Generalization. CoRR abs/2402.18396 (2024) - [i141]Ezra Erives, Bowen Jing, Tommi S. Jaakkola:
Verlet Flows: Exact-Likelihood Integrators for Flow-Based Generative Models. CoRR abs/2405.02805 (2024) - [i140]Sharut Gupta, Chenyu Wang, Yifei Wang, Tommi S. Jaakkola, Stefanie Jegelka:
In-Context Symmetries: Self-Supervised Learning through Contextual World Models. CoRR abs/2405.18193 (2024) - [i139]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 abs/2405.19276 (2024) - [i138]Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis:
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. CoRR abs/2407.03300 (2024) - [i137]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 abs/2407.04557 (2024) - [i136]Yujian Liu, Yang Zhang, Tommi S. Jaakkola, Shiyu Chang:
Revisiting Who's Harry Potter: Towards Targeted Unlearning from a Causal Intervention Perspective. CoRR abs/2407.16997 (2024) - [i135]Bowen Jing, Hannes Stärk, Tommi S. Jaakkola, Bonnie Berger:
Generative Modeling of Molecular Dynamics Trajectories. CoRR abs/2409.17808 (2024) - [i134]Menghua Wu, Umesh Padia, Sean H. Murphy, Regina Barzilay, Tommi S. Jaakkola:
Predicting perturbation targets with causal differential networks. CoRR abs/2410.03380 (2024) - [i133]Sulin Liu, Juno Nam, Andrew Campbell, Hannes Stärk, Yilun Xu, Tommi S. Jaakkola, Rafael Gómez-Bombarelli:
Think While You Generate: Discrete Diffusion with Planned Denoising. CoRR abs/2410.06264 (2024) - [i132]Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Tommaso Biancalani, Avantika Lal, Tommi S. Jaakkola, Sergey Levine, Hanchen Wang, Aviv Regev:
Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design. CoRR abs/2410.13643 (2024) - [i131]Yujian Liu, Shiyu Chang, Tommi S. Jaakkola, Yang Zhang:
Fictitious Synthetic Data Can Improve LLM Factuality via Prerequisite Learning. CoRR abs/2410.19290 (2024) - [i130]Peter Holderrieth, Yilun Xu, Tommi S. Jaakkola:
Hamiltonian Score Matching and Generative Flows. CoRR abs/2410.20470 (2024) - [i129]Julia Balla, Siddharth Mishra-Sharma, Carolina Cuesta-Lázaro, Tommi S. Jaakkola, Tess E. Smidt:
A Cosmic-Scale Benchmark for Symmetry-Preserving Data Processing. CoRR abs/2410.20516 (2024) - [i128]Peter Holderrieth, Marton Havasi, Jason Yim, Neta Shaul, Itai Gat, Tommi S. Jaakkola, Brian Karrer, Ricky T. Q. Chen, Yaron Lipman:
Generator Matching: Generative modeling with arbitrary Markov processes. CoRR abs/2410.20587 (2024) - [i127]Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi S. Jaakkola, Caroline Uhler:
An Information Criterion for Controlled Disentanglement of Multimodal Data. CoRR abs/2410.23996 (2024) - 2023
- [j35]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) - [j34]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) - [c161]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 - [c160]Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola:
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking. ICLR 2023 - [c159]Bracha Laufer-Goldshtein, Adam Fisch, Regina Barzilay, Tommi S. Jaakkola:
Efficiently Controlling Multiple Risks with Pareto Testing. ICLR 2023 - [c158]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 - [c157]Yilun Xu, Shangyuan Tong, Tommi S. Jaakkola:
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models. ICLR 2023 - [c156]Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola:
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. ICML 2023: 38566-38591 - [c155]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: 40001-40039 - [c154]Guanhua Zhang, Jiabao Ji, Yang Zhang, Mo Yu, Tommi S. Jaakkola, Shiyu Chang:
Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models. ICML 2023: 41164-41193 - [c153]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 - [c152]Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola:
Compositional Sculpting of Iterative Generative Processes. NeurIPS 2023 - [c151]Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi S. Jaakkola:
Restart Sampling for Improving Generative Processes. NeurIPS 2023 - [i126]Yilun Xu, Shangyuan Tong, Tommi S. Jaakkola:
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models. CoRR abs/2302.00670 (2023) - [i125]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 abs/2302.02277 (2023) - [i124]Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola:
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. CoRR abs/2302.04265 (2023) - [i123]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 abs/2304.00047 (2023) - [i122]Bowen Jing, Ezra Erives, Peter Pao-Huang, Gabriele Corso, Bonnie Berger, Tommi S. Jaakkola:
EigenFold: Generative Protein Structure Prediction with Diffusion Models. CoRR abs/2304.02198 (2023) - [i121]Ziming Liu, Di Luo, Yilun Xu, Tommi S. Jaakkola, Max Tegmark:
GenPhys: From Physical Processes to Generative Models. CoRR abs/2304.02637 (2023) - [i120]Guanhua Zhang, Jiabao Ji, Yang Zhang, Mo Yu, Tommi S. Jaakkola, Shiyu Chang:
Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models. CoRR abs/2304.03322 (2023) - [i119]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 abs/2304.03889 (2023) - [i118]Victor Quach, Adam Fisch, Tal Schuster, Adam Yala, Jae Ho Sohn, Tommi S. Jaakkola, Regina Barzilay:
Conformal Language Modeling. CoRR abs/2306.10193 (2023) - [i117]Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi S. Jaakkola:
Restart Sampling for Improving Generative Processes. CoRR abs/2306.14878 (2023) - [i116]Andrew Kirjner, Jason Yim, Raman Samusevich
, Tommi S. Jaakkola, Regina Barzilay, Ila Fiete:
Optimizing protein fitness using Gibbs sampling with Graph-based Smoothing. CoRR abs/2307.00494 (2023) - [i115]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 J. 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 abs/2307.08423 (2023) - [i114]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 abs/2309.08587 (2023) - [i113]Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola:
Compositional Sculpting of Iterative Generative Processes. CoRR abs/2309.16115 (2023) - [i112]Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola:
Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design. CoRR abs/2310.05764 (2023) - [i111]Xiang Fu, Tian Xie, Andrew S. Rosen
, Tommi S. Jaakkola, Jake Smith:
MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design. CoRR abs/2310.10732 (2023) - [i110]Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola:
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models. CoRR abs/2310.13102 (2023) - [i109]Xiang Fu, Albert Musaelian, Anders Johansson, Tommi S. Jaakkola, Boris Kozinsky:
Learning Interatomic Potentials at Multiple Scales. CoRR abs/2310.13756 (2023) - [i108]Chenyu Wang, Sharut Gupta, Caroline Uhler
, Tommi S. Jaakkola:
Removing Biases from Molecular Representations via Information Maximization. CoRR abs/2312.00718 (2023) - [i107]Bracha Laufer-Goldshtein, Adam Fisch, Regina Barzilay, Tommi S. Jaakkola:
Risk-Controlling Model Selection via Guided Bayesian Optimization. CoRR abs/2312.01692 (2023) - [i106]Bowen Jing, Tommi S. Jaakkola, Bonnie Berger:
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms. CoRR abs/2312.04323 (2023) - [i105]Yujian Liu, Yang Zhang, Tommi S. Jaakkola, Shiyu Chang:
Correcting Diffusion Generation through Resampling. CoRR abs/2312.06038 (2023) - 2022
- [j33]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: 340:1-340:49 (2022) - [j32]Adam Fisch, Tommi S. Jaakkola, Regina Barzilay:
Calibrated Selective Classification. Trans. Mach. Learn. Res. 2022 (2022) - [c150]Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi S. Jaakkola:
Subspace Diffusion Generative Models. ECCV (23) 2022: 274-289 - [c149]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 - [c148]Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola:
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design. ICLR 2022 - [c147]Shangyuan Tong, Timur Garipov, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola:
Adversarial Support Alignment. ICLR 2022 - [c146]Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi S. Jaakkola:
Crystal Diffusion Variational Autoencoder for Periodic Material Generation. ICLR 2022 - [c145]Yilun Xu, Hao He, Tianxiao Shen, Tommi S. Jaakkola:
Controlling Directions Orthogonal to a Classifier. ICLR 2022 - [c144]Adam Fisch, Tal Schuster, Tommi S. Jaakkola, Regina Barzilay:
Conformal Prediction Sets with Limited False Positives. ICML 2022: 6514-6532 - [c143]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Antibody-Antigen Docking and Design via Hierarchical Structure Refinement. ICML 2022: 10217-10227 - [c142]Hannes Stärk, Octavian Ganea, Lagnajit Pattanaik, Regina Barzilay, Tommi S. Jaakkola:
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction. ICML 2022: 20503-20521 - [c141]Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, Tommi S. Jaakkola:
Torsional Diffusion for Molecular Conformer Generation. NeurIPS 2022 - [c140]Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola:
Poisson Flow Generative Models. NeurIPS 2022 - [i104]Yilun Xu, Hao He, Tianxiao Shen, Tommi S. Jaakkola:
Controlling Directions Orthogonal to a Classifier. CoRR abs/2201.11259 (2022) - [i103]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 abs/2201.12406 (2022) - [i102]Hannes Stärk, Octavian-Eugen Ganea, Lagnajit Pattanaik, Regina Barzilay, Tommi S. Jaakkola:
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction. CoRR abs/2202.05146 (2022) - [i101]Adam Fisch, Tal Schuster, Tommi S. Jaakkola, Regina Barzilay:
Conformal Prediction Sets with Limited False Positives. CoRR abs/2202.07650 (2022) - [i100]Shangyuan Tong, Timur Garipov, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola:
Adversarial Support Alignment. CoRR abs/2203.08908 (2022) - [i99]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 abs/2204.10348 (2022) - [i98]Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi S. Jaakkola:
Subspace Diffusion Generative Models. CoRR abs/2205.01490 (2022) - [i97]Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, Tommi S. Jaakkola:
Torsional Diffusion for Molecular Conformer Generation. CoRR abs/2206.01729 (2022) - [i96]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. CoRR abs/2206.04119 (2022) - [i95]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement. CoRR abs/2207.06616 (2022) - [i94]Adam Fisch, Tommi S. Jaakkola, Regina Barzilay:
Calibrated Selective Classification. CoRR abs/2208.12084 (2022) - [i93]Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola:
Poisson Flow Generative Models. CoRR abs/2209.11178 (2022) - [i92]Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola:
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking. CoRR abs/2210.01776 (2022) - [i91]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 abs/2210.07237 (2022) - [i90]Bracha Laufer-Goldshtein, Adam Fisch, Regina Barzilay, Tommi S. Jaakkola:
Efficiently Controlling Multiple Risks with Pareto Testing. CoRR abs/2210.07913 (2022) - [i89]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 abs/2211.15657 (2022) - 2021
- [j31]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): e2105070118 (2021) - [c139]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: 6688-6698 - [c138]Tal Schuster, Adam Fisch, Tommi S. Jaakkola, Regina Barzilay:
Consistent Accelerated Inference via Confident Adaptive Transformers. EMNLP (1) 2021: 4962-4979 - [c137]Adam Fisch, Tal Schuster, Tommi S. Jaakkola, Regina Barzilay:
Efficient Conformal Prediction via Cascaded Inference with Expanded Admission. ICLR 2021 - [c136]Adam Fisch, Tal Schuster, Tommi S. Jaakkola, Regina Barzilay:
Few-Shot Conformal Prediction with Auxiliary Tasks. ICML 2021: 3329-3339 - [c135]Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi S. Jaakkola:
Learning Task Informed Abstractions. ICML 2021: 3480-3491 - [c134]Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov:
Information Obfuscation of Graph Neural Networks. ICML 2021: 6600-6610 - [c133]Mo Yu, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola:
Understanding Interlocking Dynamics of Cooperative Rationalization. NeurIPS 2021: 12822-12835 - [c132]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: 13757-13769 - [i88]Adam Fisch, Tal Schuster, Tommi S. Jaakkola, Regina Barzilay:
Few-shot Conformal Prediction with Auxiliary Tasks. CoRR abs/2102.08898 (2021) - [i87]Tal Schuster, Adam Fisch, Tommi S. Jaakkola, Regina Barzilay:
Consistent Accelerated Inference via Confident Adaptive Transformers. CoRR abs/2104.08803 (2021) - [i86]