Tommi S. Jaakkola

32 papers · 2006–2024 · 6 conferences · across top CS/AI conferences

Achievements

+16 more ↓

🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (6) 🗺️ Taxonomy Completionist (14) 🐣 Hot Topic Early Bird

🌈 Renaissance Researcher (6) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (9) 🏠 Conference Loyalist (20) 🏆 Keyword Champion 🌱 Topic Pioneer 🤝 Dynamic Duo (11) 🏆 Grand Slam ❓ The Questioner 📈 Trend Setter 🚀 Conference Pioneer ⚡ Prolific Year (7) 🗃️ Keyword Collector (50) 🔥 Unstoppable (6) 💎 Century Club (32)

Conferences

ICLR (20) NIPS (8) AAAI (1) AISTATS (1) ICML (1) JMLR (1)

Top co-authors

Regina Barzilay (11) Amir Globerson (5) Adam Fisch (3) Yilun Xu (3) Gabriele Corso (3) David Sontag (3) Shangyuan Tong (2) Hao He (2) Ofer Meshi (2) Dina Katabi (2)

Keywords

variational inference (4) graphical model (4) map inference (3) domain adaptation (2) linear programming relaxation (2) probabilistic modeling (2) dual optimization (2) representation learning (2) convergence rate (2) message passing (2) lp relaxation (2) bayesian inference (1) game theory (1) structured prediction (1) approximate inference (1) combinatorial optimization (1) optimal transport (1) protein-dna binding (1) algorithmic fairness (1) em algorithm (1)

Papers

Deep Confident Steps to New Pockets: Strategies for Docking Generalization ICLR 2024 Improving protein optimization with smoothed fitness landscapes ICLR 2024 Conformal Language Modeling ICLR 2024 MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design ICLR 2024 Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms ICLR 2024 Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models ICLR 2024 Removing Biases from Molecular Representations via Information Maximization ICLR 2024 Stable Target Field for Reduced Variance Score Estimation in Diffusion Models ICLR 2023 Is Conditional Generative Modeling all you need for Decision Making? ICLR 2023 Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem ICLR 2023 DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking ICLR 2023 Efficiently Controlling Multiple Risks with Pareto Testing ICLR 2023 Fundamental Limits and Tradeoffs in Invariant Representation Learning JMLR 2022 Crystal Diffusion Variational Autoencoder for Periodic Material Generation ICLR 2022 Adversarial Support Alignment ICLR 2022 Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking ICLR 2022 Controlling Directions Orthogonal to a Classifier ICLR 2022 Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design ICLR 2022 Efficient Conformal Prediction via Cascaded Inference with Expanded Admission ICLR 2021 Oblique Decision Trees from Derivatives of ReLU Networks ICLR 2020 Towards Optimal Transport with Global Invariances AISTATS 2019 Bidirectional Inference Networks:A Class of Deep Bayesian Networks for Health Profiling AAAI 2019 Towards Robust, Locally Linear Deep Networks ICLR 2019 Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture ICML 2017 Convergence Rate Analysis of MAP Coordinate Minimization Algorithms NIPS 2012 More data means less inference: A pseudo-max approach to structured learning NIPS 2010 Clusters and Coarse Partitions in LP Relaxations NIPS 2008 New Outer Bounds on the Marginal Polytope NIPS 2007 Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations NIPS 2007 Parameter Expanded Variational Bayesian Methods NIPS 2006 Approximate inference using planar graph decomposition NIPS 2006 Game Theoretic Algorithms for Protein-DNA binding NIPS 2006