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Understanding Interlocking Dynamics of Cooperative Rationalization


Oct 26, 2021
Mo Yu, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola

* Accepted at NeurIPS 2021 

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GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles


Jun 08, 2021
Octavian-Eugen Ganea, Lagnajit Pattanaik, Connor W. Coley, Regina Barzilay, Klavs F. Jensen, William H. Green, Tommi S. Jaakkola


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NeuraCrypt: Hiding Private Health Data via Random Neural Networks for Public Training


Jun 04, 2021
Adam Yala, Homa Esfahanizadeh, Rafael G. L. D' Oliveira, Ken R. Duffy, Manya Ghobadi, Tommi S. Jaakkola, Vinod Vaikuntanathan, Regina Barzilay, Muriel Medard


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Fundamental Limits and Tradeoffs in Invariant Representation Learning


Dec 19, 2020
Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar


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Invariant Rationalization


Mar 22, 2020
Shiyu Chang, Yang Zhang, Mo Yu, Tommi S. Jaakkola

* 10 pages 

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Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces


Nov 06, 2019
David Alvarez-Melis, Youssef Mroueh, Tommi S. Jaakkola


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Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control


Oct 29, 2019
Mo Yu, Shiyu Chang, Yang Zhang, Tommi S. Jaakkola

* Accepted by EMNLP 2019 

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A Game Theoretic Approach to Class-wise Selective Rationalization


Oct 28, 2019
Shiyu Chang, Yang Zhang, Mo Yu, Tommi S. Jaakkola

* Accepted by Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada 

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Learning to Make Generalizable and Diverse Predictions for Retrosynthesis


Oct 21, 2019
Benson Chen, Tianxiao Shen, Tommi S. Jaakkola, Regina Barzilay


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Locally Constant Networks


Sep 30, 2019
Guang-He Lee, Tommi S. Jaakkola


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Towards Robust, Locally Linear Deep Networks


Jul 07, 2019
Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola

* Published in International Conference on Learning Representations (ICLR), 2019 

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A Stratified Approach to Robustness for Randomly Smoothed Classifiers


Jun 12, 2019
Guang-He Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola


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Functional Transparency for Structured Data: a Game-Theoretic Approach


Feb 26, 2019
Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola


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Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling


Feb 06, 2019
Hao Wang, Chengzhi Mao, Hao He, Mingmin Zhao, Tommi S. Jaakkola, Dina Katabi

* Appeared at AAAI 2019 

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Gromov-Wasserstein Alignment of Word Embedding Spaces


Aug 31, 2018
David Alvarez-Melis, Tommi S. Jaakkola

* EMNLP 2018 

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Game-Theoretic Interpretability for Temporal Modeling


Jun 30, 2018
Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola


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Towards Optimal Transport with Global Invariances


Jun 25, 2018
David Alvarez-Melis, Stefanie Jegelka, Tommi S. Jaakkola


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On the Robustness of Interpretability Methods


Jun 21, 2018
David Alvarez-Melis, Tommi S. Jaakkola

* presented at 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018), Stockholm, Sweden 

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Towards Robust Interpretability with Self-Explaining Neural Networks


Jun 20, 2018
David Alvarez-Melis, Tommi S. Jaakkola


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Structured Optimal Transport


Dec 17, 2017
David Alvarez-Melis, Tommi S. Jaakkola, Stefanie Jegelka


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A causal framework for explaining the predictions of black-box sequence-to-sequence models


Nov 14, 2017
David Alvarez-Melis, Tommi S. Jaakkola

* 12 Pages, EMNLP 2017 

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From random walks to distances on unweighted graphs


Nov 02, 2015
Tatsunori B. Hashimoto, Yi Sun, Tommi S. Jaakkola

* To appear in NIPS 2015 

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Word, graph and manifold embedding from Markov processes


Sep 18, 2015
Tatsunori B. Hashimoto, David Alvarez-Melis, Tommi S. Jaakkola


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Metric recovery from directed unweighted graphs


Nov 20, 2014
Tatsunori B. Hashimoto, Yi Sun, Tommi S. Jaakkola

* Poster at NIPS workshop on networks. Submitted to AISTATS 2015 

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Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models


Sep 26, 2013
Jean Honorio, Tommi S. Jaakkola

* Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013) 

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Computing Upper and Lower Bounds on Likelihoods in Intractable Networks


Feb 13, 2013
Tommi S. Jaakkola, Michael I. Jordan

* Appears in Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence (UAI1996) 

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Tractable Bayesian Learning of Tree Belief Networks


Jan 16, 2013
Marina Meila, Tommi S. Jaakkola

* Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000) 

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Feature Selection and Dualities in Maximum Entropy Discrimination


Jan 16, 2013
Tony S. Jebara, Tommi S. Jaakkola

* Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000) 

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A New Class of Upper Bounds on the Log Partition Function


Dec 12, 2012
Martin Wainwright, Tommi S. Jaakkola, Alan Willsky

* Appears in Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI2002) 

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Unsupervised Active Learning in Large Domains


Dec 12, 2012
Harald Steck, Tommi S. Jaakkola

* Appears in Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI2002) 

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