SymDrift: One-Shot Generative Modeling under Symmetries
Advances in Neural Information Processing Systems (NeurIPS) 2026.
MLS Lab · University of Stuttgart
Publications
Publications by Mathias Niepert, group members, and collaborators. The archive also includes work preceding the MLS group.
2026
Distillation of Foundation Models for Time-dependent PDEs
Advances in Neural Information Processing Systems (NeurIPS) 2026.
Geometry Meets Physics: Data-Efficient Pre-Training for Unstructured Neural PDE Solvers
Advances in Neural Information Processing Systems (NeurIPS) 2026.
Robust generative transition-state models for unseen chemistry
Nature Computational Science, 2026.
SMART: Scalable Mesh-free Aerodynamic Simulations from Raw Geometries using a Transformer-based Surrogate Model
In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026.
Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining
In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026.
Logical Guidance for the Exact Composition of Diffusion Models
In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026.
FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation
In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026.
Protein Fold Classification at Scale: Benchmarking and Pretraining
In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026. Oral presentation.
Preference-Based Gradient Estimation for ML-Guided Approximate Combinatorial Optimization
Transactions on Machine Learning Research (TMLR), 2026.
Adaptive Transition-State Refinement with Learned Equilibrium Flows
Journal of Chemical Information and Modeling (JCIM), 2026.
Performance of Universal Machine-Learned Potentials with Explicit Long-Range Interactions in Biomolecular Simulations
ACS Journal of Chemical Theory and Computation (JCTC), 2026.
Adaptive Width Neural Networks
International Conference on Learning Representations (ICLR) 2026.
FACET: A Fragment-Aware Conformer Ensemble Transformer
International Conference on Learning Representations (ICLR) 2026.
2025
Learning (Approximately) Equivariant Networks via Constrained Optimization
Advances in Neural Information Processing Systems (NeurIPS) 2025. oral presentation (top 0.3% of submissions)
Rao-Blackwell Gradient Estimators for Equivariant Denoising Diffusion
Advances in Neural Information Processing Systems (NeurIPS) 2025.
CALM-PDE: Continuous and Adaptive Convolutions for Latent Space Modeling of Time-dependent PDEs
Advances in Neural Information Processing Systems (NeurIPS) 2025. spotlight presentation (top 3% of submissions)
ExGra-Med: Extended Context Graph Alignment for Medical Vision-Language Models
Advances in Neural Information Processing Systems (NeurIPS) 2025.
How Many Tokens Do 3D Point Cloud Transformer Architectures Really Need?
Advances in Neural Information Processing Systems (NeurIPS) 2025.
From Fragments to Geometry: A Unified Graph Transformer for Molecular Representation from Conformer Ensembles
Generative AI and Biology (GenBio) Workshop @ ICML 2025.
Enriched Instruction-Following Graph Alignment for Efficient Medical Vision-Language Models
Workshop on Multi-modal Foundation Models and Large Language Models for Life Sciences @ ICML 2025.
Prompt Engineering Techniques for Language Model Reasoning Lack Replicability
Transactions on Machine Learning Research (TMLR), 2025.
How Many Tokens Do 3D Point Cloud Transformer Architectures Really Need?
Workshop on Efficient Systems for Foundation Models @ ICML 2025.
Physics-Informed Weakly-Supervised Learning for Interatomic Potentials
In Proceedings of the 42nd International Conference on Machine Learning (ICML 2025).
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
In Proceedings of the 42nd International Conference on Machine Learning (ICML 2025).
On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation
In Proceedings of the 42nd International Conference on Machine Learning (ICML 2025).
Tractable Transformers for Flexible Conditional Generation
In Proceedings of the 42nd International Conference on Machine Learning (ICML 2025).
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
In Proceedings of the 42nd International Conference on Machine Learning (ICML 2025).
Symmetry-Preserving Diffusion Models via Target Symmetrization
Workshop on Deep Generative Models in Machine Learning: Theory, Principle and Efficacy @ ICLR 2025.
LOGLO-FNO: Efficient Learning of Local and Global Features in Fourier Neural Operators
Transactions on Machine Learning Research (TMLR), 2025. Workshop on Machine Learning Multiscale Processes @ ICLR 2025. (oral presentation)
Adaptive Physics-informed Neural Networks: A Survey
Transactions on Machine Learning Research (TMLR 2025).
Learning to Discretize Denoising Diffusion ODEs
In Proceedings of the 13th International Conference on Learning Representations (ICLR 2025). selected for an oral presentation (top 1.8% of submissions)
Active Learning for Neural PDE Solvers
In Proceedings of the 13th International Conference on Learning Representations (ICLR 2025).
Discrete Copula Diffusion
In Proceedings of the 13th International Conference on Learning Representations (ICLR 2025).
2024
Survey: Adaptive Physics-informed Neural Networks
Workshop on Foundation Models for Science @ NeurIPS 2024.
MolMix: A Simple Yet Effective Baseline for Multimodal Molecular Representation Learning
Workshop on Machine Learning for Structural Biology @ NeurIPS 2024.
Active Learning for Neural PDE Solvers
Workshop on Data-driven and Differentiable Simulations, Surrogates, and Solvers @ NeurIPS 2024.
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
Advances in Neural Information Processing Systems (NeurIPS 2024).
Accelerating Transformers with Spectrum-Preserving Token Merging
Advances in Neural Information Processing Systems (NeurIPS 2024).
Probabilistic Graph Rewiring via Virtual Nodes
Advances in Neural Information Processing Systems (NeurIPS 2024).
Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model
In Proceedings of the 16th Asian Conference on Machine Learning (ACML 2024).
Physics-Informed Weakly Supervised Learning for Interatomic Potentials
AI for Science Workshop @ ICML 2024.
L2XGNN: Learning to Explain Graph Neural Networks
Machine Learning Journal and ECML 2024.
Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations
In Proceedings of the 41st International Conference on Machine Learning (ICML 2024).
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks
In Proceedings of the 41st International Conference on Machine Learning (ICML 2024).
Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials
NPJ Computational Materials.
Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent PDEs
AI for Differential Equations in Science Workshop @ ICLR 2024.
Vectorized Conditional Neural Fields for Computational Fluid Dynamics
1st Workshop on Machine Learning for Fluid Dynamics (ERCOFTAC), Paris, 8 March 2024.
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks
In Proceedings of the 12th International Conference on Learning Representations (ICLR 2024).
Image Inpainting via Tractable Steering of Diffusion Models
In Proceedings of the 12th International Conference on Learning Representations (ICLR 2024).
Probabilistically Rewired Message-Passing Neural Networks
In Proceedings of the 12th International Conference on Learning Representations (ICLR 2024).
2023
On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation
Workshop on Robustness of Few-shot and Zero-shot Learning in Large Foundation Models @ NeurIPS 2023.
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching
Advances in Neural Information Processing Systems (NeurIPS 2023).
Learning Disentangled Discrete Representations
In Proceedings of the 34th European Conference on Machine Learning (ECML 2023).
Learning Neural PDE Solvers with Parameter-Guided Channel Attention
In Proceedings of the 40th International Conference on Machine Learning (ICML 2023).
Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models
In Proceedings of the 37th Conference on Artificial Intelligence (AAAI 2023).
SIMPLE: A Gradient Estimator for k-Subset Sampling
In Proceedings of the 11th International Conference on Learning Representations (ICLR 2023).
State-Regularized Recurrent Neural Networks to Extract Automata and Explain Predictions
Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 06, 2023.
Probabilistic Task-Adaptive Graph Rewiring
Workshop on Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators @ ICML 2023.
Approximate Answering of Graph Queries
Compendium of Neurosymbolic Artificial Intelligence.
2022
SIMPLE: A Gradient Estimator for k-Subset Sampling
SoCal ML and NLP Symposium, 2022.
Channel-Attention-Based PDE Parameter Embeddings for SciML
Machine Learning and the Physical Sciences Workshop (ML4PS) @ NeurIPS.
HyperFNO: Improving the Generalization Behavior of Fourier Neural Operators
Machine Learning and the Physical Sciences Workshop (ML4PS) @ NeurIPS.
Joint Multilingual Knowledge Graph Completion and Alignment
In Findings of Empirical Natural Language Processing (Findings EMNLP 2022).
Ordered Subgraph Aggregation Networks
Advances in Neural Information Processing Systems (NeurIPS 2022).
Behavioral Testing of Knowledge Graph Embedding Models for Link Prediction
BlackboxNLP Workshop co-located with EMNLP 2022.
PDEBench: An Extensive Benchmark for Scientific Machine Learning
Advances in Neural Information Processing Systems (NeurIPS 2022).
MILIE: Modular & Iterative Multilingual Open Information Extraction
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022.
BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022.
AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 2022.
2021
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions
Advances in Neural Information Processing Systems (NeurIPS 2021).
Efficient Learning of Discrete-Continuous Computation Graphs
Advances in Neural Information Processing Systems (NeurIPS 2021).
User Profiling by Network Observers
International Conference on emerging Networking EXperiments and Technologies (ACM CoNext 2021).
Behavioral Testing of Knowledge Graph Embedding Models for Link Prediction
International Conference on Automated Knowledge Base Construction (AKBC 2021).
Wayfinder: towards automatically deriving optimal OS configurations
12th ACM SIGOPS Asia-Pacific Workshop on Systems (APSys 2021).
VEGN: Variant Effect Prediction with Graph Neural Networks
ICML Workshop on Computational Biology (WCB).
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
In Proceedings of the Ninth International Conference on Learning Representations (ICLR 2021).
Explaining Neural Matrix Factorization with Gradient Rollback
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2021).
Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2021).
Learning Representations of Missing Data using Graph Neural Networks for Predicting Patient Outcomes
AAAI'21 Workshop on Deep Learning on Graphs: Methods and Applications (DLG-AAAI'21)
Learning Sparsity of Representations with Discrete Latent Variables
In Proceedings of the International Joint Conference on Neural Networks (IJCNN 2021).
Interpreting Node Embedding with Text-labeled Graphs
In Proceedings of the International Joint Conference on Neural Networks (IJCNN 2021).
2020
Tractability through Exchangeability: The Statistics of Lifting
In An Introduction to Probabilistic Lifted Inference, MIT Press.
Lifted Markov Chain Monte Carlo
In An Introduction to Probabilistic Lifted Inference, MIT Press.
Explaining Neural Matrix Factorization with Gradient Rollback
Women in Machine Learning Workshop @ NeurIPS.
RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems
IEEE Transactions on Neural Networks and Learning Systems.
TransRev: Modeling Reviews as Translations from Users to Items
preprint In Proceedings of the European Conference on Information Retrieval (ECIR).
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
preprint
2019
Attending to Future Tokens For Bidirectional Sequence Generation
In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Hong Kong.
Cross-Sentence N-ary Relation Extraction using Lower-Arity Universal Schemas
In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Hong Kong.
State-Regularized Recurrent Neural Networks
In Proceedings of the 36th International Conference on Machine Learning (ICML), Long Beach, USA.
State-Regularized Recurrent Neural Networks
BlackboxNLP Workshop co-located with ACL 2019, Florence, Italy.
Learning Discrete Structures for Graph Neural Networks
In Proceedings of the 36th International Conference on Machine Learning (ICML), Long Beach, USA.
A Comparative Study of Distributional and Symbolic Paradigms for Relational Learning
In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), Macao, China.
Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
In Proceedings of the 1st Conference on Automated Knowledge Base Construction (AKBC), Amherst, Massachusetts.
Graph Structure Learning for GCNs
ICLR Workshop on Representation Learning on Graphs and Manifolds, New Orleans, USA.
MMKG: Multi-Modal Knowledge Graphs
In Proceedings of the 16th Extended Semantic Web Conference (ESWC), Portoroz, Slovenia.
2018
LRMM: Learning to Recommend with Missing Modalities
In Proceedings of the Conference on Empirical Methods in Natural Language Processing ( EMNLP ), Brussels, Belgium.
Learning Sequence Encoders for Temporal Knowledge Base Completion
In Proceedings of the Conference on Empirical Methods in Natural Language Processing ( EMNLP ), Brussels, Belgium.
KBLRN: End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features
In Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence ( UAI ), Monterey, California.
Towards A Spectrum of Graph Convolutional Networks
In Proceedings of the 1st IEEE Data Science Workshop, Lausanne, Switzerland.
Contextual Hourglass Networks for Segmentation and Density Estimation
Proceedings of the 1st International Conference on Medical Imaging with Deep Learning ( MIDL ), Amsterdam, The Netherlands. (winner of NVIDIA best poster award)
Learning Short-Cut Connections for Object Counting
Proceedings of the 29th British Machine Vision Conference ( BMVC ), Newcastle upon Tyne, UK.
On Embeddings as an Alternative Paradigm for Relational Learning
Proceedings of the 8th International Workshop on Statistical Relational AI ( StaRAI ), Stockholm, Sweden, 2018.
Representation Learning for Resource Usage Prediction
Proceedings of the 1st SysML Conference, Stanford, USA.
BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism
preprint
Representation Learning for Visual-Relational Knowledge Graphs
KDD Deep Learning Day, London, UK. preprint
2017
Learning Graph Representations with Embedding Propagation
Advances in Neural Information Processing Systems ( NIPS ), Long Beach, USA, 2017.
Net2vec: Deep Learning for the Network
Proceedings of the Workshop on Big Data Analytics and Machine Learning for Data Communication Networks, Big-DAMA, SIGCOMM 2017
Network Data Monetization Using Net2Vec
Proceedings of the Conference of the ACM Special Interest Group on Data Communication (SIGCOMM) 2017.
An Infrastructure for Probabilistic Reasoning with Web Ontologies
Semantic Web Journal, 2017.
Scalable Regression Tree Learning in Data Streams
2016
Discriminative Gaifman Models
Advances in Neural Information Processing Systems ( NIPS ), Barcelona, Spain, 2016.
Learning Convolutional Neural Networks for Graphs
In Proceedings of the 33rd International Conference on Machine Learning ( ICML ), New York City, 2016.
2015
Learning and Inference in Tractable Probabilistic Knowledge Bases
Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence. ( UAI ), Amsterdam, The Netherlands, 2015
Lifted Probabilistic Inference for Asymmetric Graphical Models
Proceedings of the 29th Conference on Artificial Intelligence. (oral presentation) ( AAAI ), Austin, Texas, 2015.
2014
Generalized Conditional Independence and Decomposition Cognizant Curvature: Implications for Function Optimization
NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning ( DISCML ) 2014.
Out of Many, One: Unifying Web-Extracted Knowledge Bases
NIPS Workshop on Automated Knowledge Base Construction ( AKBC ) 2014.
Exchangeable Variable Models
In Proceedings of the 31st International Conference on Machine Learning ( ICML ), Beijing, China, 2014. (also accepted for presentation at the ICML Learning Tractable Probabilistic Models Workshop )
Tractability through Exchangeability: A New Perspective on Efficient Probabilistic Inference
In Proceedings of the 28th Conference on Artificial Intelligence ( AAAI ), Quebec City, Canada, 2014. (one of 5 papers nominated for the AAAI outstanding paper award) ; also accepted for presentation at the SIGMOD/PODS Big Uncertain Data Workshop )
Tractable Probabilistic Knowledge Bases: Wikipedia and Beyond
In Proceedings of the 4th Workshop on Statistical Relational AI ( StaRAI ), Quebec City, Canada, 2014.
LODE: Linking Digital Humanities Content to the Web of Data
In Proceedings of the 14th ACM/IEEE Joint Conference on Digital Libraries ( JCDL ), London, UK, 2014.
On the completeness of the semigraphoid axioms for deriving arbitrary from saturated conditional independence statements
Information Processing Letters, 2014.
Completeness and Optimality in Ontology Alignment Debugging
Proceedings of the 9th International Workshop on Ontology Matching, Trento, Italy, 2014.
2013
Symmetry-Aware Marginal Density Estimation
In Proceedings of the 27th Conference on Artificial Intelligence ( AAAI ), Bellevue, Washington, USA, 2013. (also accepted for presentation at the Statistical Relational AI workshop )
The Conditional Independence Implication Problem: A Lattice-Theoretic Approach
Artificial Intelligence 202:29-51, 2013.
Statistical Relational Data Integration for Information Extraction
Reasoning Web, Springer, Heidelberg, 2013.
Computing Incoherence Explanations for Learned Ontologies
In Proceedings of the 7th International Conference on Web Reasoning and Rule Systems, Mannheim, Germany, 2013.
Integrating Open and Closed Information Extraction: Challenges and First Steps
In Proceedings of the NLP & DBpedia workshop co-located with ISWC, Sydney, Australia, 2013.
RockIt: Exploiting Parallelism and Symmetry for MAP Inference in Statistical Relational Models
In Proceedings of the 27th Conference on Artificial Intelligence ( AAAI ), Bellevue, Washington, USA, 2013. (also accepted for presentation at the Statistical Relational AI workshop )
2012
Lifted Probabilistic Inference: An MCMC Perspective
In Proceedings of the 2nd International Workshop on Statistical Relational AI ( StaR AI ), Catalina Island, USA, 2012.
Markov Chains on Orbits of Permutation Groups
In Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence ( UAI ), Catalina Island, USA, 2012.
Towards Distributed MCMC Inference in Probabilistic Knowledge Bases
NAACL-HLT Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction ( AKBC-WEKEX ), Montreal, Canada, 2012.
Probabilistic Optimization of Semantic Process Model Matching
In Proceedings of the 10th International Conference on Business Process Management ( BPM ), Tallinn, Estonia, 2012.
Towards Activity Recognition Using Probabilistic Description Logics
In Proceedings of the AAAI workshops, Toronto, Canada, 2012.
2011
Reasoning under Uncertainty with Log-Linear Description Logics
In Proceedings of the 7th International Workshop on Uncertain Reasoning for the Semantic Web (URSW) at ISWC, Bonn, Germany, 2011.
Fine-Grained Sentiment Analysis with Structural Features
In Proceedings of the 5th International Joint Conference on Natural Language Processing (IJCNLP), Chiang Mai, Thailand, 2011. (best paper award)
Log-Linear Description Logics
In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI), Barcelona, Spain, 2011. (selected for oral presentation)
Coherent Top-k Ontology Alignment for OWL EL
In Proceedings of the 5th International Conference on Scalable Uncertainty Management (SUM), Dayton, Ohio, Springer-Verlag, 2011.
Recognizing Interleaved and Concurrent Activities Using Qualitative and Quantitative Temporal Relationships
Pervasive and Mobile Computing, Volume 7, Issue 6, Elsevier, 2011.
ELOG: A Probabilistic Reasoner for OWL EL
In Proceedings of the 5th International Conference on Web Reasoning and Rule Systems (RR), Galway, Ireland, Springer-Verlag, 2011.
Probabilistic-Logical Web Data Integration
In Reasoning Web: 7th International Summer School 2011, Galway, Ireland, Springer-Verlag, 2011.
Statistical Schema Induction
In Proceedings of the 8th Extended Semantic Web Conference (ESWC), Heraklion, Greece, Springer-Verlag, 2011.
Recognizing Interleaved and Concurrent Activities: A Statistical Relational Approach
In Proceedings of the 9th IEEE International Conference on Pervasive Computing and Communications (PerCom), Seattle, Washington, 2011.
2010
A Delayed Column Generation Strategy for Exact k -Bounded MAP Inference in Markov Logic Networks
In Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI), Catalina Island, California, AUAI Press, 2010.
A Probabilistic-Logical Framework for Ontology Matching
In Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI), Atlanta, Georgia, AAAI Press, 2010. (selected as exceptional top 4% paper)
CODI: Combinatorial Optimization for Data Integration
In Proceedings of the 5th International Workshop on Ontology Matching (OM), Shanghai, China, 2010.
Crowdsourcing the Assembly of Concept Hierarchies
In Proceedings of the 10th ACM/IEEE Joint Conference on Digital Libraries (JCDL), Gold Coast, Australia, ACM Press, 2010.
BRAMBLE: A Web-based Framework for Interactive RDF-Graph Visualisation
International Semantic Web Conference (ISWC) 2010. (demo paper)
Towards Collaboratively Learning and Populating Ontologies for the Social-Semantic Web
SIGWEB Newsletter, Spring 2010, ACM Press.
Leveraging Terminological Structure for Object Reconciliation
In Proceedings of the 7th Extended Semantic Web Conference (ESWC), Heraklion, Greece, Springer-Verlag, 2010. (best paper award)
Logical and Algorithmic Properties of Stable Conditional Independence
International Journal of Approximate Reasoning, Volume 51, Issue 5, pages 531-543, 2010.
From Encyclopedia to Ontology: Toward A Dynamic Representation of the Discipline of Philosophy
Synthese , Springer-Verlag, 2010.
Thesaurus Extension Using Web Search Engines
In Proceedings of the 12th International Conference on Asia-Pacific Digital Libraries (ICADL), Gold Coast, Australia, Springer-Verlag, 2010.
2009
Logical Inference Algorithms and Matrix Representations for Probabilistic Conditional Independence
In Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI), Montreal, Canada, pages 428-435, AUAI Press, 2009.
Working the Crowd: Design Principles and Early Lessons from the Social-Semantic Web
In Proceedings of the Workshop on Web 3.0: Merging Semantic Web and Social Web - (SW)^2 at ACM Hypertext, Turin, Italy, 2009.
2008
On the Conditional Independence Implication Problem: A Lattice-Theoretic Approach
In Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence (UAI), Helsinki, Finland, pages 435-443, AUAI Press, 2008. (best student paper runner-up award)
The World is Not Flat: Expertise and InPhO
Selected papers from the Ninth Annual WebWise Conference. First Monday , Volume 13, Number 8, 2008.
2007
A Dynamic Ontology for a Dynamic Reference Work
In Proceedings of the 7th ACM/IEEE Joint Conference on Digital Libraries (JCDL), Vancouver, British Columbia, pages 288-297, ACM Press, 2007.
Information reviewed 26 September 2026 · Author bibliography