Tommi S. Jaakkola
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Computer scientist, Massachusetts Institute of Technology
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(Suggest an Edit or Addition)Tommi S. Jaakkola's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- An Introduction to Variational Methods for Graphical Models (1999) (4081)
- Exploiting Generative Models in Discriminative Classifiers (1998) (1672)
- Maximum-Margin Matrix Factorization (2004) (1151)
- On the Convergence of Stochastic Iterative Dynamic Programming Algorithms (1993) (937)
- Junction Tree Variational Autoencoder for Molecular Graph Generation (2018) (872)
- A Deep Learning Approach to Antibiotic Discovery (2020) (832)
- Weighted Low-Rank Approximations (2003) (803)
- Serial Regulation of Transcriptional Regulators in the Yeast Cell Cycle (2001) (710)
- MAP estimation via agreement on trees: message-passing and linear programming (2005) (709)
- Partially labeled classification with Markov random walks (2001) (688)
- Computational discovery of gene modules and regulatory networks (2003) (660)
- Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms (2000) (641)
- Rationalizing Neural Predictions (2016) (640)
- Style Transfer from Non-Parallel Text by Cross-Alignment (2017) (639)
- Analyzing Learned Molecular Representations for Property Prediction (2019) (615)
- Bayesian parameter estimation via variational methods (2000) (610)
- Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation (2012) (598)
- A Discriminative Framework for Detecting Remote Protein Homologies (2000) (568)
- Towards Robust Interpretability with Self-Explaining Neural Networks (2018) (559)
- Using the Fisher Kernel Method to Detect Remote Protein Homologies (1999) (490)
- Fast optimal leaf ordering for hierarchical clustering (2001) (465)
- A new class of upper bounds on the log partition function (2002) (462)
- Mean Field Theory for Sigmoid Belief Networks (1996) (458)
- Using Graphical Models and Genomic Expression Data to Statistically Validate Models of Genetic Regulatory Networks (2000) (451)
- Learning Without State-Estimation in Partially Observable Markovian Decision Processes (1994) (430)
- Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems (1994) (427)
- Prediction of Organic Reaction Outcomes Using Machine Learning (2017) (427)
- Discovery of non-directional and directional pioneer transcription factors by modeling DNase profile magnitude and shape (2014) (395)
- Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations (2007) (379)
- Reinforcement Learning with Soft State Aggregation (1994) (367)
- Tutorial on variational approximation methods (2000) (340)
- Combining Location and Expression Data for Principled Discovery of Genetic Regulatory Network Models (2001) (326)
- A graph-convolutional neural network model for the prediction of chemical reactivity† †Electronic supplementary information (ESI) available: Additional model and dataset details, results, discussion, and ref. 38 and 39. See DOI: 10.1039/c8sc04228d (2018) (323)
- On the Robustness of Interpretability Methods (2018) (319)
- Tightening LP Relaxations for MAP using Message Passing (2008) (317)
- Maximum Entropy Discrimination (1999) (294)
- Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction. (2017) (289)
- Continuous Representations of Time-Series Gene Expression Data (2003) (285)
- Probabilistic kernel regression models (1999) (282)
- Tree-based reparameterization framework for analysis of sum-product and related algorithms (2003) (278)
- Gromov-Wasserstein Alignment of Word Embedding Spaces (2018) (242)
- Tree-reweighted belief propagation algorithms and approximate ML estimation by pseudo-moment matching (2003) (236)
- MAP estimation via agreement on (hyper)trees: Message-passing and linear programming (2005) (231)
- A new approach to analyzing gene expression time series data (2002) (229)
- A variational approach to Bayesian logistic regression problems and their extensions (1996) (224)
- Learning Bayesian Network Structure using LP Relaxations (2010) (217)
- Generative Models for Graph-Based Protein Design (2019) (213)
- Dual Decomposition for Parsing with Non-Projective Head Automata (2010) (192)
- Variational Probabilistic Inference and the QMR-DT Network (2011) (189)
- On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing (2010) (187)
- Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network (2017) (186)
- Physical Network Models (2004) (181)
- Generalization and Representational Limits of Graph Neural Networks (2020) (179)
- Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture (2017) (176)
- Learning Multimodal Graph-to-Graph Translation for Molecular Optimization (2018) (166)
- A causal framework for explaining the predictions of black-box sequence-to-sequence models (2017) (165)
- Introduction to dual composition for inference (2011) (159)
- New Outer Bounds on the Marginal Polytope (2007) (158)
- Tree consistency and bounds on the performance of the max-product algorithm and its generalizations (2004) (144)
- Hierarchical Generation of Molecular Graphs using Structural Motifs (2020) (142)
- Molding CNNs for text: non-linear, non-consecutive convolutions (2015) (141)
- Comparing the continuous representation of time-series expression profiles to identify differentially expressed genes (2003) (141)
- Bayesian Network Approach to Cell Signaling Pathway Modeling (2002) (138)
- K-ary Clustering with Optimal Leaf Ordering for Gene Expression Data (2002) (137)
- Generalization Error Bounds for Collaborative Prediction with Low-Rank Matrices (2004) (128)
- Maximum-likelihood estimation of optimal scaling factors for expression array normalization (2001) (124)
- Information Regularization with Partially Labeled Data (2002) (124)
- Variational methods for inference and estimation in graphical models (1997) (122)
- Deriving Neural Architectures from Sequence and Graph Kernels (2017) (119)
- Low-Rank Tensors for Scoring Dependency Structures (2014) (115)
- Ten Pairs to Tag – Multilingual POS Tagging via Coarse Mapping between Embeddings (2016) (107)
- Collaborative future event recommendation (2010) (106)
- Validation and refinement of gene-regulatory pathways on a network of physical interactions (2005) (105)
- On the Dirichlet Prior and Bayesian Regularization (2002) (102)
- Multi-Objective Molecule Generation using Interpretable Substructures (2020) (102)
- High-resolution computational models of genome binding events (2006) (98)
- Approximating Posterior Distributions in Belief Networks Using Mixtures (1997) (98)
- Tree-structured decoding with doubly-recurrent neural networks (2016) (96)
- Current and Future Roles of Artificial Intelligence in Medicinal Chemistry Synthesis (2020) (96)
- Invariant Rationalization (2020) (94)
- Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers (2019) (91)
- Tractable Bayesian learning of tree belief networks (2000) (90)
- Feature Selection and Dualities in Maximum Entropy Discrimination (2000) (90)
- Aspect-augmented Adversarial Networks for Domain Adaptation (2017) (89)
- On Information Regularization (2002) (89)
- Learning Efficiently with Approximate Inference via Dual Losses (2010) (87)
- Bayesian Methods for Elucidating Genetic Regulatory Networks (2002) (84)
- On the Partition Function and Random Maximum A-Posteriori Perturbations (2012) (84)
- Sequence to Better Sequence: Continuous Revision of Combinatorial Structures (2017) (84)
- Semi-supervised Question Retrieval with Gated Convolutions (2015) (84)
- Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control (2019) (83)
- Tree Block Coordinate Descent for MAP in Graphical Models (2009) (81)
- Computing upper and lower bounds on likelihoods in intractable networks (1996) (79)
- Perspectives on ENCODE (2020) (79)
- Approximate inference in graphical models using lp relaxations (2010) (77)
- Improving the Mean Field Approximation Via the Use of Mixture Distributions (1999) (75)
- Word Embeddings as Metric Recovery in Semantic Spaces (2016) (75)
- A Deep Learning Approach to Antibiotic Discovery (2020) (74)
- Tree-based reparameterization for approximate inference on loopy graphs (2001) (72)
- Steps Toward Deep Kernel Methods from Infinite Neural Networks (2015) (71)
- Using term informativeness for named entity detection (2005) (70)
- EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction (2022) (69)
- Grounding Language for Transfer in Deep Reinforcement Learning (2017) (69)
- An Unsupervised Method for Uncovering Morphological Chains (2015) (67)
- Online Learning of Non-stationary Sequences (2003) (64)
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples (2018) (59)
- Approximate inference using planar graph decomposition (2006) (56)
- Torsional Diffusion for Molecular Conformer Generation (2022) (56)
- Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking (2021) (56)
- On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations (2013) (55)
- Greed is Good if Randomized: New Inference for Dependency Parsing (2014) (55)
- Towards Optimal Transport with Global Invariances (2018) (55)
- Discovering homotypic binding events at high spatial resolution (2010) (54)
- Deep learning identifies synergistic drug combinations for treating COVID-19 (2021) (52)
- Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design (2021) (49)
- Blank Language Models (2020) (49)
- Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem (2022) (48)
- Parameter Expanded Variational Bayesian Methods (2006) (48)
- Bias-Corrected Bootstrap and Model Uncertainty (2003) (48)
- Distributed Information Regularization on Graphs (2004) (48)
- Crystal Diffusion Variational Autoencoder for Periodic Material Generation (2021) (48)
- Structured Optimal Transport (2017) (46)
- GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles (2021) (45)
- Controlling privacy in recommender systems (2014) (45)
- Continuation Methods for Mixing Heterogenous Sources (2002) (45)
- Recursive Algorithms for Approximating Probabilities in Graphical Models (1996) (44)
- Approximate inference using conditional entropy decompositions (2007) (43)
- DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking (2022) (43)
- Learning Population-Level Diffusions with Generative RNNs (2016) (42)
- Kernel Expansions with Unlabeled Examples (2000) (42)
- Automated Discovery of Functional Generality of Human Gene Expression Programs (2007) (41)
- Path-Augmented Graph Transformer Network (2019) (41)
- Convergent Propagation Algorithms via Oriented Trees (2007) (38)
- Educating Text Autoencoders: Latent Representation Guidance via Denoising (2019) (38)
- Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees (2014) (37)
- Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models (2022) (36)
- Principal Differences Analysis: Interpretable Characterization of Differences between Distributions (2015) (33)
- Convergence Rate Analysis of MAP Coordinate Minimization Algorithms (2012) (33)
- Exact MAP Estimates by (Hyper)tree Agreement (2002) (33)
- Towards Robust, Locally Linear Deep Networks (2019) (33)
- Direct Optimization through arg max for Discrete Variational Auto-Encoder (2018) (32)
- Variational methods and the QMR-DT database (1998) (32)
- Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks (1995) (32)
- Sequentially Fitting "Inclusive" Trees for Inference in Noisy-OR Networks (2000) (32)
- Benchmarking AlphaFold‐enabled molecular docking predictions for antibiotic discovery (2022) (31)
- Steps to Excellence: Simple Inference with Refined Scoring of Dependency Trees (2014) (31)
- Learning to Make Generalizable and Diverse Predictions for Retrosynthesis (2019) (30)
- A Game Theoretic Approach to Class-wise Selective Rationalization (2019) (30)
- Variational probabilistic inference and the QMR-DT database (1998) (30)
- Efficient Conformal Prediction via Cascaded Inference with Expanded Admission (2021) (27)
- Generative models for molecular discovery: Recent advances and challenges (2022) (27)
- Active Information Retrieval (2001) (26)
- Are Learned Molecular Representations Ready For Prime Time? (2019) (26)
- Stable Mixing of Complete and Incomplete Information (2001) (26)
- Few-shot Conformal Prediction with Auxiliary Tasks (2021) (25)
- Predictive Discretization during Model Selection (2004) (25)
- Learning with Maximum A-Posteriori Perturbation Models (2014) (25)
- Learning Task Informed Abstractions (2021) (25)
- Time series analysis of gene expression and location data (2003) (24)
- Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models (2013) (24)
- Clusters and Coarse Partitions in LP Relaxations (2008) (24)
- Physical network models and multi-source data integration (2003) (23)
- More data means less inference: A pseudo-max approach to structured learning (2010) (23)
- Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions (2013) (22)
- Integration of Principal-Component-Analysis and Streamline Information for the History Matching of Channelized Reservoirs (2014) (22)
- Unsupervised Active Learning in Large Domains (2002) (22)
- Deep Transfer in Reinforcement Learning by Language Grounding (2017) (22)
- Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces (2019) (22)
- Hierarchical Graph-to-Graph Translation for Molecules (2019) (22)
- Consistent Accelerated Inference via Confident Adaptive Transformers (2021) (21)
- Domain Extrapolation via Regret Minimization (2020) (21)
- Metric recovery from directed unweighted graphs (2014) (20)
- Composing Molecules with Multiple Property Constraints (2020) (20)
- Is Conditional Generative Modeling all you need for Decision-Making? (2022) (19)
- Optimal Transport Graph Neural Networks (2020) (18)
- Mean Field Theory for Sigmoid Belief NetworksMean Field Theory for Sigmoid Belief (1996) (17)
- From random walks to distances on unweighted graphs (2015) (17)
- Modeling the Combinatorial Functions of Multiple Transcription Factors (2005) (16)
- Multi-resolution Autoregressive Graph-to-Graph Translation for Molecules (2019) (16)
- Information Obfuscation of Graph Neural Networks (2020) (16)
- Learning Tree Structured Potential Games (2016) (15)
- Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations (2022) (15)
- Improving Molecular Design by Stochastic Iterative Target Augmentation (2020) (15)
- Functional Transparency for Structured Data: a Game-Theoretic Approach (2019) (15)
- Bayesian parameter estimation through variational methods (2008) (15)
- A synergistic DNA logic predicts genome-wide chromatin accessibility (2016) (14)
- Poisson Flow Generative Models (2022) (14)
- Integration of PCA with a Novel Machine Learning Method for Reparameterization and Assisted History Matching Geologically Complex Reservoirs (2015) (14)
- On Measure Concentration of Random Maximum A-Posteriori Perturbations (2013) (14)
- Active Boundary Annotation using Random MAP Perturbations (2014) (13)
- Denoising Bodies to Titles: Retrieving Similar Questions with Recurrent Convolutional Models (2015) (13)
- Managing the 802.11 Energy/Performance Tradeoff with Machine Learning (2004) (13)
- Learning Representations that Support Robust Transfer of Predictors (2021) (12)
- Fundamental Limits and Tradeoffs in Invariant Representation Learning (2020) (12)
- Understanding Interlocking Dynamics of Cooperative Rationalization (2021) (12)
- Learning population-level diffusions with generative recurrent networks (2016) (12)
- Generalized Low-Rank Approximations (2003) (11)
- Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling (2019) (11)
- Solving graph compression via optimal transport (2019) (11)
- Clustering and efficient use of unlabeled examples (2001) (10)
- Learning to refine text based recommendations (2016) (10)
- Correction to Analyzing Learned Molecular Representations for Property Prediction (2019) (10)
- Structured Prediction: From Gaussian Perturbations to Linear-Time Principled Algorithms (2015) (10)
- Enforcing Predictive Invariance across Structured Biomedical Domains (2020) (9)
- NeuraCrypt: Hiding Private Health Data via Random Neural Networks for Public Training (2021) (9)
- Data-Dependent Regularization (2006) (9)
- Linear Dependent Dimensionality Reduction (2003) (9)
- Semi-supervised analysis of gene expression profiles for lineage-specific development in the Caenorhabditis elegans embryo (2006) (9)
- Word, graph and manifold embedding from Markov processes (2015) (9)
- Oblique Decision Trees from Derivatives of ReLU Networks (2019) (9)
- Large-Margin Matrix Factorization (2004) (8)
- Primal-Dual methods for sparse constrained matrix completion (2012) (8)
- Learning Optimal Interventions (2016) (8)
- Simulate Time-integrated Coarse-grained Molecular Dynamics with Geometric Machine Learning (2022) (7)
- A Stratified Approach to Robustness for Randomly Smoothed Classifiers (2019) (7)
- Automatic Feature Induction for Text Classification (2002) (7)
- Local Aggregative Games (2017) (7)
- Antibody-Antigen Docking and Design via Hierarchical Structure Refinement (2022) (7)
- Learning Corresponded Rationales for Text Matching (2018) (7)
- High Dimensional Inference With Random Maximum A-Posteriori Perturbations (2016) (7)
- Thinking Outside the Box: Enhancing Science Teaching by Combining (Instead of Contrasting) Laboratory and Simulation Activities (2012) (6)
- Adaptive Invariance for Molecule Property Prediction (2020) (6)
- Controlling Directions Orthogonal to a Classifier (2022) (6)
- Sparse Matrix Factorization of Gene Expression Data (2001) (6)
- Tree-based reparameterization analysis of belief propagation and related algorithms for approximate inference on graphs with cycles (2002) (6)
- Graph Adversarial Networks: Protecting Information against Adversarial Attacks (2020) (6)
- Hierarchical Dirichlet Process-Based Models For Discovery of Cross-species Mammalian Gene Expression (2007) (6)
- Self-Supervised Learning of Appliance Usage (2020) (6)
- Statistical Learning under Nonstationary Mixing Processes (2015) (6)
- Modeling Persistent Trends in Distributions (2015) (5)
- Game-Theoretic Interpretability for Temporal Modeling (2018) (5)
- Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis (2020) (5)
- Conformal Prediction Sets with Limited False Positives (2022) (5)
- A Unified Framework for Consistency of Regularized Loss Minimizers (2014) (5)
- Fragment-based Sequential Translation for Molecular Optimization (2021) (4)
- Erratum: High-resolution computational models of genome binding events (2006) (4)
- Sparse Matrix Factorization for Analyzing Gene Expression Patterns (2001) (4)
- Lineage-based identification of cellular states and expression programs (2012) (4)
- Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy (2013) (4)
- Adversarial Support Alignment (2022) (4)
- Game Theoretic Algorithms for Protein-DNA binding (2006) (4)
- PFGM++: Unlocking the Potential of Physics-Inspired Generative Models (2023) (3)
- Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (2005) (2012) (3)
- Syfer: Neural Obfuscation for Private Data Release (2022) (3)
- Modeling Drug Combinations based on Molecular Structures and Biological Targets (2020) (3)
- Inferring regulatory networks from multiple sources of genomic data (2004) (3)
- CRAFT: ClusteR-specific Assorted Feature selecTion (2015) (3)
- Focused Inference (2005) (3)
- Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement (2022) (3)
- Latent Space Secrets of Denoising Text-Autoencoders (2019) (3)
- Generating Molecules with Optimized Aqueous Solubility using Iterative Graph Translation (2021) (3)
- Approximate Expectation Propagation for Bayesian Inference on Large-scale Problems (2005) (2)
- Modeling Trends in Distributions (2015) (2)
- Calibrated Selective Classification (2022) (2)
- Stable Target Field for Reduced Variance Score Estimation in Diffusion Models (2023) (2)
- 6.867 Machine Learning, Fall 2002 (2002) (2)
- Locally Constant Networks (2019) (2)
- DNA Binding and Games (2006) (2)
- SE(3) diffusion model with application to protein backbone generation (2023) (2)
- Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (2010) (2)
- Discovering Synergistic Drug Combinations for COVID with Biological Bottleneck Models (2020) (2)
- Table 2 (Supplemental): Complete data for all 100 expression programs discovered by GeneProgram from the Novartis Gene Atlas v2 (2007) (1)
- Table 1 (Supplemental): Summary of expression programs discovered by GeneProgram from Novartis Tissue Atlas v2 data (2007) (1)
- Dna binding economies (2007) (1)
- Predicting deliberative outcomes (2020) (1)
- On Iteratively Constraining the Marginal Polytope for Approximate Inference and MAP (2007) (1)
- Efficiently Controlling Multiple Risks with Pareto Testing (2022) (1)
- END-TO-END RIGID PROTEIN DOCKING (2021) (1)
- The Kaali giant meteorite fall in the Finnish-Estonian folklore. (1988) (1)
- On the Statistical Efficiency of $\ell_{1,p}$ Multi-Task Learning of Gaussian Graphical Models (2012) (1)
- To appear in "Semi-supervised learning", O. Chappelle, B. Scholkopf, and A. Zien, Eds., 2005 (2005) (1)
- Using Deep Reinforcement Learning to Generate Rationales for Molecules (2018) (1)
- LATION FOR MOLECULAR OPTIMIZATION (2019) (1)
- Fragment-based Sequential Translation for Molecular Optimization FRAGMENT-BASED SEQUENTIAL TRANSLATION FOR MOLECULAR OPTIMIZATION (2021) (1)
- T REE-STRUCTURED DECODING WITH DOUBLY-RECURRENT NEURAL NETWORKS (2017) (1)
- Analysis of signaling pathways in human T-cells using Bayesian network modeling of single cell data (2004) (1)
- Relaxed Conformal Prediction Cascades for Efficient Inference Over Many Labels (2020) (1)
- Iterative Target Augmentation for Effective Conditional Generation (2019) (0)
- EigenFold: Generative Protein Structure Prediction with Diffusion Models (2023) (0)
- Virtual Node Graph Neural Network for Full Phonon Prediction (2023) (0)
- Adaptive Invariant Risk Minimization for Molecule Property Prediction (2020) (0)
- Vc Dimension Further Information 3.3 Optimization Algorithms 3 Learning from Data (1996) (0)
- The Benefits of Pairwise Discriminators for Adversarial Training (2020) (0)
- Uncertainty in artificial intelligence : proceedings of the Twenty-first Conference (2005) : July 26-29, 2005, Edinburgh, Scotland (2005) (0)
- A Comprehensive Approach to Fusion for Microsensor Networks: Distributed and Hierarchical Inference, Communication, and Adaption REPORT DOCUMENTATION PAGE (2000) (0)
- GenPhys: From Physical Processes to Generative Models (2023) (0)
- Denoising Improves Latent Space Geometry in Text Autoencoders (2019) (0)
- IMPROVING THE MEAN FIELD APPROXIMATIONVIA THE USE OF MIXTURE (1998) (0)
- Learning with Online Constraints : Shifting Concepts and Active Learning (0)
- MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES (1996) (0)
- Author Correction: Perspectives on ENCODE (2022) (0)
- Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models (2023) (0)
- DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models (2023) (0)
- Automated System for Knowledge-Based Continuous Organic Synthesis: Data-Driven Pathway Design and Validation (Invited Lecture) (2018) (0)
- A ug 2 00 5 1 MAP estimation via agreement on trees : Message-passing and linear programming (0)
- An Unsupervised Method for Uncovering Morphological Chains (Open Access, Publisher's Version) (2015) (0)
- Special Issue on the Fifth European Workshop on Probabilistic Graphical Models (PGM-2010) (2012) (0)
- Tradeo s between generative and discriminative hidden Markov models (2006) (0)
- Adaptive Information Filtering with Minimal Instruction MIT 2000-08 Progress Report : January 1 , 2002 — June 30 , 2002 Tommi Jaakkola and Tomaso Poggio Project Overview (2003) (0)
- Predicting Synergistic Drug Combinations for COVID with Biological Bottleneck Models (2020) (0)
- Author Correction: Expanded encyclopaedias of DNA elements in the human and mouse genomes (2022) (0)
- Tree-based reparameterization forapproximate estimation on loopy graphsMartin (2001) (0)
- Generalized Low-Rank Approximations Nathan Srebro and Tommi Jaakkola (2003) (0)
- T ORSIONAL D IFFUSION FOR M OLECULAR C ONFORMER G ENERATION (2022) (0)
- 6 . 867 Machine Learning Lecture 20 (2010) (0)
- Controlling privacy in recommender systems Citation (2015) (0)
- Bidirectional Inference Networks with Application to Health Profiling (2019) (0)
- PEOPL: Characterizing Privately Encoded Open Datasets with Public Labels (2023) (0)
- ANALYSIS OF $sup 55$Fe PRODUCED BY NUCLEAR TESTS AND ITS ENRICHMENT IN FINNISH LAPPS. (1969) (0)
- A re-examination of Danjon's observations of the planet Mercury. (1969) (0)
- STAT 538 Handout 5 February 21 , 2008 Variational bounds for graphical models (0)
- Food Adulteration Detection Using Neural Networks by Youyang Gu (2016) (0)
- Blind protein-ligand docking with diffusion-based deep generative models. (2023) (0)
- 3 Extractive Rationale Generation (2016) (0)
- Small scale validation cont (2010) (0)
- Structured Optimal Transport : Supplementary Material (2018) (0)
- Improving Multi-class Text Classification with Naive Bayes Improving Multi-class Text Classification with Naive Bayes Contents (2001) (0)
- Maximum Likelihood Markov Hypertrees (2001) (0)
- Alignment Based Matching Networks for One-Shot Classification and Open-Set Recognition (2018) (0)
- Artificial Intelligence and Statistics 2001 : proceedings of the eighth international workshop : January 4-7, 2001, Key West, Florida (2001) (0)
- Supplementary materials and proofs (2015) (0)
- A Dealing with di ↵ erent samples sizes and dimensions (2019) (0)
- Bringing Simulations to the Classroom: Teachers’ Perspectives (2021) (0)
- Training and test performance : sampling (2004) (0)
- Strategic Prediction with Latent Aggregative Games (2019) (0)
- 6.867 Machine Learning Lecture 16 (2010) (0)
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