← Authors

Tommi S. Jaakkola

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

Achievements

πŸ—ΊοΈ Taxonomy Completionist (14) 🐝 Cross-Pollinator (9) πŸƒ Academic Marathon (18) 🌍 Conference Polyglot (6) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (9) 🏠 Conference Loyalist (20) πŸ† Keyword Champion 🌱 Topic Pioneer 🀝 Dynamic Duo (11) πŸ† Grand Slam ❓ The Questioner πŸ“ˆ Trend Setter πŸš€ Conference Pioneer ⚑ Prolific Year (7) πŸ—ƒοΈ Keyword Collector (50) πŸ”₯ Unstoppable (6) πŸ’Ž 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