Timezone: »
Author Information
Amir Globerson (Tel Aviv University, Google)
Amir Globerson is senior lecturer at the School of Engineering and Computer Science at the Hebrew University. He received a PhD in computational neuroscience from the Hebrew University, and was a Rothschild postdoctoral fellow at MIT. He joined the Hebrew University in 2008. His research interests include graphical models and probabilistic inference, convex optimization, robust learning and natural language processing.
Tommi Jaakkola (MIT)
Tommi Jaakkola is a professor of Electrical Engineering and Computer Science at MIT. He received an M.Sc. degree in theoretical physics from Helsinki University of Technology, and Ph.D. from MIT in computational neuroscience. Following a Sloan postdoctoral fellowship in computational molecular biology, he joined the MIT faculty in 1998. His research interests include statistical inference, graphical models, and large scale modern estimation problems with predominantly incomplete data.
More from the Same Authors
-
2021 Spotlight: GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles »
Octavian Ganea · Lagnajit Pattanaik · Connor Coley · Regina Barzilay · Klavs Jensen · William Green · Tommi Jaakkola -
2021 : Consistent Accelerated Inference via Confident Adaptive Transformers »
Tal Schuster · Adam Fisch · Tommi Jaakkola · Regina Barzilay -
2021 : Fragment-Based Sequential Translation for Molecular Optimization »
Benson Chen · Xiang Fu · Regina Barzilay · Tommi Jaakkola -
2021 : Crystal Diffusion Variational Autoencoder for Periodic Material Generation »
Tian Xie · Xiang Fu · Octavian Ganea · Regina Barzilay · Tommi Jaakkola -
2022 : DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking »
Gabriele Corso · Hannes Stärk · Bowen Jing · Regina Barzilay · Tommi Jaakkola -
2022 : Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations »
Xiang Fu · Zhenghao Wu · Wujie Wang · Tian Xie · Sinan Keten · Rafael Gomez-Bombarelli · Tommi Jaakkola -
2022 : DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking »
Gabriele Corso · Hannes Stärk · Bowen Jing · Regina Barzilay · Tommi Jaakkola -
2022 : Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem »
Jason Yim · Brian L Trippe · Doug Tischer · David Baker · Tamara Broderick · Regina Barzilay · Tommi Jaakkola -
2022 : DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking »
Gabriele Corso · Hannes Stärk · Bowen Jing · Regina Barzilay · Tommi Jaakkola -
2022 : Is Conditional Generative Modeling all you need for Decision-Making? »
Anurag Ajay · Yilun Du · Abhi Gupta · Josh Tenenbaum · Tommi Jaakkola · Pulkit Agrawal -
2022 : Molecular Docking with Diffusion Generative Models »
Gabriele Corso · Hannes Stärk · Bowen Jing · Regina Barzilay · Tommi Jaakkola -
2022 Spotlight: Poisson Flow Generative Models »
Yilun Xu · Ziming Liu · Max Tegmark · Tommi Jaakkola -
2022 Spotlight: Lightning Talks 6B-1 »
Yushun Zhang · Duc Nguyen · Jiancong Xiao · Wei Jiang · Yaohua Wang · Yilun Xu · Zhen LI · Anderson Ye Zhang · Ziming Liu · Fangyi Zhang · Gilles Stoltz · Congliang Chen · Gang Li · Yanbo Fan · Ruoyu Sun · Naichen Shi · Yibo Wang · Ming Lin · Max Tegmark · Lijun Zhang · Jue Wang · Ruoyu Sun · Tommi Jaakkola · Senzhang Wang · Zhi-Quan Luo · Xiuyu Sun · Zhi-Quan Luo · Tianbao Yang · Rong Jin -
2022 : DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking »
Gabriele Corso · Hannes Stärk · Bowen Jing · Regina Barzilay · Tommi Jaakkola -
2022 : Invited Talk: Tommi Jaakkola »
Tommi Jaakkola -
2022 Poster: Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens »
Elad Ben Avraham · Roei Herzig · Karttikeya Mangalam · Amir Bar · Anna Rohrbach · Leonid Karlinsky · Trevor Darrell · Amir Globerson -
2022 Poster: Torsional Diffusion for Molecular Conformer Generation »
Bowen Jing · Gabriele Corso · Jeffrey Chang · Regina Barzilay · Tommi Jaakkola -
2022 Poster: Visual Prompting via Image Inpainting »
Amir Bar · Yossi Gandelsman · Trevor Darrell · Amir Globerson · Alexei Efros -
2022 Poster: Poisson Flow Generative Models »
Yilun Xu · Ziming Liu · Max Tegmark · Tommi Jaakkola -
2021 : Consistent Accelerated Inference via Confident Adaptive Transformers »
Tal Schuster · Adam Fisch · Tommi Jaakkola · Regina Barzilay -
2021 Poster: A Theoretical Analysis of Fine-tuning with Linear Teachers »
Gal Shachaf · Alon Brutzkus · Amir Globerson -
2021 Poster: Understanding Interlocking Dynamics of Cooperative Rationalization »
Mo Yu · Yang Zhang · Shiyu Chang · Tommi Jaakkola -
2021 Poster: GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles »
Octavian Ganea · Lagnajit Pattanaik · Connor Coley · Regina Barzilay · Klavs Jensen · William Green · Tommi Jaakkola -
2020 Poster: Regularizing Towards Permutation Invariance In Recurrent Models »
Edo Cohen-Karlik · Avichai Ben David · Amir Globerson -
2019 Poster: Solving graph compression via optimal transport »
Vikas Garg · Tommi Jaakkola -
2019 Poster: Generative Models for Graph-Based Protein Design »
John Ingraham · Vikas Garg · Regina Barzilay · Tommi Jaakkola -
2019 Poster: Direct Optimization through $\arg \max$ for Discrete Variational Auto-Encoder »
Guy Lorberbom · Andreea Gane · Tommi Jaakkola · Tamir Hazan -
2019 Poster: Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers »
Guang-He Lee · Yang Yuan · Shiyu Chang · Tommi Jaakkola -
2019 Poster: A Game Theoretic Approach to Class-wise Selective Rationalization »
Shiyu Chang · Yang Zhang · Mo Yu · Tommi Jaakkola -
2018 : Invited Talk Session 3 »
Alexandre Tkatchenko · Tommi Jaakkola · Jennifer Wei -
2018 Poster: Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction »
Roei Herzig · Moshiko Raboh · Gal Chechik · Jonathan Berant · Amir Globerson -
2018 Poster: Towards Robust Interpretability with Self-Explaining Neural Networks »
David Alvarez-Melis · Tommi Jaakkola -
2017 Poster: Local Aggregative Games »
Vikas Garg · Tommi Jaakkola -
2017 Poster: Style Transfer from Non-Parallel Text by Cross-Alignment »
Tianxiao Shen · Tao Lei · Regina Barzilay · Tommi Jaakkola -
2017 Spotlight: Style Transfer from Non-parallel Text by Cross-Alignment »
Tianxiao Shen · Tao Lei · Regina Barzilay · Tommi Jaakkola -
2017 Poster: Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network »
Wengong Jin · Connor Coley · Regina Barzilay · Tommi Jaakkola -
2017 Poster: Robust Conditional Probabilities »
Yoav Wald · Amir Globerson -
2016 Poster: Optimal Tagging with Markov Chain Optimization »
Nir Rosenfeld · Amir Globerson -
2016 Poster: Learning Tree Structured Potential Games »
Vikas Garg · Tommi Jaakkola -
2015 Poster: From random walks to distances on unweighted graphs »
Tatsunori Hashimoto · Yi Sun · Tommi Jaakkola -
2015 Poster: Principal Differences Analysis: Interpretable Characterization of Differences between Distributions »
Jonas Mueller · Tommi Jaakkola -
2014 Poster: Controlling privacy in recommender systems »
Yu Xin · Tommi Jaakkola -
2013 Poster: Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions »
Tamir Hazan · Subhransu Maji · Joseph Keshet · Tommi Jaakkola -
2013 Poster: On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations »
Tamir Hazan · Subhransu Maji · Tommi Jaakkola -
2012 Workshop: Machine Learning Approaches to Mobile Context Awareness »
Katherine Ellis · Gert Lanckriet · Tommi Jaakkola · Lenny Grokop -
2012 Poster: Convergence Rate Analysis of MAP Coordinate Minimization Algorithms »
Ofer Meshi · Tommi Jaakkola · Amir Globerson -
2011 Session: Spotlight Session 3 »
Amir Globerson -
2011 Session: Oral Session 3 »
Amir Globerson -
2011 Tutorial: Linear Programming Relaxations for Graphical Models »
Amir Globerson · Tommi Jaakkola -
2010 Spotlight: More data means less inference: A pseudo-max approach to structured learning »
David Sontag · Ofer Meshi · Tommi Jaakkola · Amir Globerson -
2010 Poster: More data means less inference: A pseudo-max approach to structured learning »
David Sontag · Ofer Meshi · Tommi Jaakkola · Amir Globerson -
2009 Workshop: Approximate Learning of Large Scale Graphical Models »
Russ Salakhutdinov · Amir Globerson · David Sontag -
2009 Poster: An LP View of the M-best MAP problem »
Menachem Fromer · Amir Globerson -
2009 Oral: An LP View of the M-Best MAP Problem »
Menachem Fromer · Amir Globerson -
2008 Workshop: Approximate inference - how far have we come? »
Amir Globerson · David Sontag · Tommi Jaakkola -
2008 Poster: Clusters and Coarse Partitions in LP Relaxations »
David Sontag · Amir Globerson · Tommi Jaakkola -
2008 Spotlight: Clusters and Coarse Partitions in LP Relaxations »
David Sontag · Amir Globerson · Tommi Jaakkola -
2007 Poster: Convex Learning with Invariances »
Choon Hui Teo · Amir Globerson · Sam T Roweis · Alexander Smola -
2007 Oral: New Outer Bounds on the Marginal Polytope »
David Sontag · Tommi Jaakkola -
2007 Poster: New Outer Bounds on the Marginal Polytope »
David Sontag · Tommi Jaakkola -
2007 Spotlight: Convex Learning with Invariances »
Choon Hui Teo · Amir Globerson · Sam T Roweis · Alexander Smola -
2007 Poster: Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations »
Amir Globerson · Tommi Jaakkola -
2006 Poster: Approximate inference using planar graph decomposition »
Amir Globerson · Tommi Jaakkola -
2006 Poster: Game Theoretic Algorithms for Protein-DNA binding »
Luis Perez-Breva · Luis E Ortiz · Chen-Hsiang Yeang · Tommi Jaakkola -
2006 Spotlight: Game Theoretic Algorithms for Protein-DNA binding »
Luis Perez-Breva · Luis E Ortiz · Chen-Hsiang Yeang · Tommi Jaakkola -
2006 Poster: Parameter Expanded Variational Bayesian Methods »
Yuan (Alan) Qi · Tommi Jaakkola