Volker Tresp

Affiliations:
  • Ludwig Maximilian University of Munich, Germany


According to our database1, Volker Tresp authored at least 286 papers between 1990 and 2024.

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Bibliography

2024
Quantum Architecture Search with Unsupervised Representation Learning.
CoRR, 2024

2023
The Tensor Brain: A Unified Theory of Perception, Memory, and Semantic Decoding.
Neural Comput., February, 2023

Understanding and Improving In-Context Learning on Vision-language Models.
CoRR, 2023

Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation.
CoRR, 2023

SPOT! Revisiting Video-Language Models for Event Understanding.
CoRR, 2023

Zero-Shot Relational Learning on Temporal Knowledge Graphs with Large Language Models.
CoRR, 2023

Enhancing Multimodal Compositional Reasoning of Visual Language Models with Generative Negative Mining.
CoRR, 2023

GraphextQA: A Benchmark for Evaluating Graph-Enhanced Large Language Models.
CoRR, 2023

GenTKG: Generative Forecasting on Temporal Knowledge Graph.
CoRR, 2023

FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning.
CoRR, 2023

FedPop: Federated Population-based Hyperparameter Tuning.
CoRR, 2023

A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models.
CoRR, 2023

Exploring Link Prediction over Hyper-Relational Temporal Knowledge Graphs Enhanced with Time-Invariant Relational Knowledge.
CoRR, 2023

Can Vision-Language Models be a Good Guesser? Exploring VLMs for Times and Location Reasoning.
CoRR, 2023

GRAtt-VIS: Gated Residual Attention for Auto Rectifying Video Instance Segmentation.
CoRR, 2023

Modeling the evolution of temporal knowledge graphs with uncertainty.
CoRR, 2023

Adversarial Attacks on Tables with Entity Swap.
Proceedings of the Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, August 28, 2023

ForecastTKGQuestions: A Benchmark for Temporal Question Answering and Forecasting over Temporal Knowledge Graphs.
Proceedings of the Semantic Web - ISWC 2023, 2023

Workshop Summary: Quantum Machine Learning.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Differentiable Quantum Architecture Search for Quantum Reinforcement Learning.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs Using Confidence-Augmented Reinforcement Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Explaining Deep Neural Networks for Bearing Fault Detection with Vibration Concepts.
Proceedings of the 21st IEEE International Conference on Industrial Informatics, 2023

Adaptive Multi-Resolution Attention with Linear Complexity.
Proceedings of the International Joint Conference on Neural Networks, 2023

Learning Meta-Representations of One-shot Relations for Temporal Knowledge Graph Link Prediction.
Proceedings of the International Joint Conference on Neural Networks, 2023

Multi-event Video-Text Retrieval.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Do DALL-E and Flamingo Understand Each Other?
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Does Your Model Think Like an Engineer? Explainable AI for Bearing Fault Detection with Deep Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

QNEAT: Natural Evolution of Variational Quantum Circuit Architecture.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

A Knowledge Graph Perspective on Supply Chain Resilience.
Proceedings of the Second International Workshop on Linked Data-driven Resilience Research 2023 co-located with Extended Semantic Web Conference 2023 (ESWC 2023), 2023

ECOLA: Enhancing Temporal Knowledge Embeddings with Contextualized Language Representations.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

InstanceFormer: An Online Video Instance Segmentation Framework.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Bringing Light Into the Dark: A Large-Scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

CL-CrossVQA: A Continual Learning Benchmark for Cross-Domain Visual Question Answering.
CoRR, 2022

Few-Shot Inductive Learning on Temporal Knowledge Graphs using Concept-Aware Information.
CoRR, 2022

Forecasting Question Answering over Temporal Knowledge Graphs.
CoRR, 2022

Continuous Temporal Graph Networks for Event-Based Graph Data.
CoRR, 2022

FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation.
CoRR, 2022

Learning Meta Representations of One-shot Relations for Temporal Knowledge Graph Link Prediction.
CoRR, 2022

Enhanced Temporal Knowledge Embeddings with Contextualized Language Representations.
CoRR, 2022

A Unified Framework for Rank-based Evaluation Metrics for Link Prediction in Knowledge Graphs.
CoRR, 2022

On Calibration of Graph Neural Networks for Node Classification.
Proceedings of the International Joint Conference on Neural Networks, 2022

Improving Inductive Link Prediction Using Hyper-Relational Facts (Extended Abstract).
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

Named Entity Recognition in Industrial Tables using Tabular Language Models.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: EMNLP 2022 - Industry Track, Abu Dhabi, UAE, December 7, 2022

Relationformer: A Unified Framework for Image-to-Graph Generation.
Proceedings of the Computer Vision - ECCV 2022, 2022

SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness.
Proceedings of the Computer Vision - ECCV 2022, 2022

Are Vision Transformers Robust to Patch Perturbations?
Proceedings of the Computer Vision - ECCV 2022, 2022

Biologically Inspired Neural Path Finding.
Proceedings of the Brain Informatics - 15th International Conference, 2022

Towards Data-Free Domain Generalization.
Proceedings of the Asian Conference on Machine Learning, 2022

TempCaps: A Capsule Network-based Embedding Model for Temporal Knowledge Graph Completion.
Proceedings of the Sixth Workshop on Structured Prediction for NLP, 2022

Improving Scene Graph Classification by Exploiting Knowledge from Texts.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphs.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings.
J. Mach. Learn. Res., 2021

A Simple But Powerful Graph Encoder for Temporal Knowledge Graph Completion.
CoRR, 2021

Adversarial Examples on Segmentation Models Can be Easy to Transfer.
CoRR, 2021

Generating Table Vector Representations.
CoRR, 2021

COLUMBUS: Automated Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption.
CoRR, 2021

Scenes and Surroundings: Scene Graph Generation using Relation Transformer.
CoRR, 2021

Improving Visual Reasoning by Exploiting The Knowledge in Texts.
CoRR, 2021

Temporal Knowledge Graph Forecasting with Neural ODE.
CoRR, 2021

NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification.
Proceedings of the SSDBM 2021: 33rd International Conference on Scientific and Statistical Database Management, 2021

Graphhopper: Multi-hop Scene Graph Reasoning for Visual Question Answering.
Proceedings of the Semantic Web - ISWC 2021 - 20th International Semantic Web Conference, 2021

Improving Inductive Link Prediction Using Hyper-relational Facts.
Proceedings of the Semantic Web - ISWC 2021 - 20th International Semantic Web Conference, 2021

Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models.
Proceedings of the Machine Learning for Healthcare Conference, 2021

Semantics for Global and Local Interpretation of Deep Convolutional Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2021

Mutual Information State Intrinsic Control.
Proceedings of the 9th International Conference on Learning Representations, 2021

Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs.
Proceedings of the 9th International Conference on Learning Representations, 2021

Effective and Efficient Vote Attack on Capsule Networks.
Proceedings of the 9th International Conference on Learning Representations, 2021

Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning.
Proceedings of the 9th IEEE International Conference on Healthcare Informatics, 2021

Neural Multi-hop Reasoning with Logical Rules on Biomedical Knowledge Graphs.
Proceedings of the Semantic Web - 18th International Conference, 2021

Time-dependent Entity Embedding is not All You Need: A Re-evaluation of Temporal Knowledge Graph Completion Models under a Unified Framework.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Learning Neural Ordinary Equations for Forecasting Future Links on Temporal Knowledge Graphs.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Active Learning for Entity Alignment.
Proceedings of the Advances in Information Retrieval, 2021

Capsule Network Is Not More Robust Than Convolutional Network.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

OODformer: Out-Of-Distribution Detection Transformer.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Causal Inference under Networked Interference and Intervention Policy Enhancement.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Description-based Label Attention Classifier for Explainable ICD-9 Classification.
Proceedings of the Seventh Workshop on Noisy User-generated Text, 2021

Classification by Attention: Scene Graph Classification with Prior Knowledge.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Few-Shot One-Class Classification via Meta-Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Representation Learning for the Semantic Web.
J. Web Semant., 2020

Relational and Fine-Grained Argument Mining.
Datenbank-Spektrum, 2020

xERTE: Explainable Reasoning on Temporal Knowledge Graphs for Forecasting Future Links.
CoRR, 2020

Interpretable Graph Capsule Networks for Object Recognition.
CoRR, 2020

Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing.
CoRR, 2020

Scene Graph Reasoning for Visual Question Answering.
CoRR, 2020

Relation Transformer Network.
CoRR, 2020

Graph Hawkes Network for Reasoning on Temporal Knowledge Graphs.
CoRR, 2020

Causal Inference under Networked Interference.
CoRR, 2020

Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods with Adjusted Mean Rank.
CoRR, 2020

Mutual Information-based State-Control for Intrinsically Motivated Reinforcement Learning.
CoRR, 2020

The Tensor Brain: Semantic Decoding for Perception and Memory.
CoRR, 2020

Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs.
CoRR, 2020

Quantum Machine Learning Algorithm for Knowledge Graphs.
CoRR, 2020

Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods.
Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2020

Improving Visual Relation Detection using Depth Maps.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

ARCADe: A Rapid Continual Anomaly Detector.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score.
Proceedings of the 8th IEEE International Conference on Healthcare Informatics, 2020

Human-Machine Collaboration for Medical Image Segmentation.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Künstliche Intelligenz - Die dritte Welle.
Proceedings of the 50. Jahrestagung der Gesellschaft für Informatik, INFORMATIK 2020 - Back to the Future, Karlsruhe, Germany, 28. September, 2020

An Unsupervised Joint System for Text Generation from Knowledge Graphs and Semantic Parsing.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

DyERNIE: Dynamic Evolution of Riemannian Manifold Embeddings for Temporal Knowledge Graph Completion.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned.
Proceedings of the Advances in Information Retrieval, 2020

Search for Better Students to Learn Distilled Knowledge.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Improving the Robustness of Capsule Networks to Image Affine Transformations.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Controllable Multi-Character Psychology-Oriented Story Generation.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Learning with Temporal Knowledge Graphs.
Proceedings of the CIKM 2020 Workshops co-located with 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020

CSSA'20: Workshop on Combining Symbolic and Sub-Symbolic Methods and their Applications.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Graph Hawkes Neural Network for Forecasting on Temporal Knowledge Graphs.
Proceedings of the Conference on Automated Knowledge Base Construction, 2020

Introspective Learning by Distilling Knowledge from Online Self-explanation.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

Reasoning on Knowledge Graphs with Debate Dynamics.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Embedding models for episodic knowledge graphs.
J. Web Semant., 2019

Neural Network Memorization Dissection.
CoRR, 2019

Walking the Tightrope: An Investigation of the Convolutional Autoencoder Bottleneck.
CoRR, 2019

Contextual Prediction Difference Analysis.
CoRR, 2019

Semantics for Global and Local Interpretation of Deep Neural Networks.
CoRR, 2019

Push it to the Limit: Discover Edge-Cases in Image Data with Autoencoders.
CoRR, 2019

Saliency Methods for Explaining Adversarial Attacks.
CoRR, 2019

Improving Visual Relation Detection using Depth Maps.
CoRR, 2019

Variational Quantum Circuit Model for Knowledge Graphs Embedding.
CoRR, 2019

Curiosity-Driven Experience Prioritization via Density Estimation.
CoRR, 2019

Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation.
Proceedings of the Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data, 2019

Remaining Useful Life Estimation for Unknown Motors Using a Hybrid Modeling Approach.
Proceedings of the 17th IEEE International Conference on Industrial Informatics, 2019

Maximum Entropy-Regularized Multi-Goal Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Categorical EHR Imputation with Generative Adversarial Nets.
Proceedings of the 2019 IEEE International Conference on Healthcare Informatics, 2019

A Recommender System for Complex Real-World Applications with Nonlinear Dependencies and Knowledge Graph Context.
Proceedings of the Semantic Web - 16th International Conference, 2019

2018
Relational Models.
Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

Adaptive Knowledge Propagation in Web Ontologies.
ACM Trans. Web, 2018

Embedding Models for Episodic Memory.
CoRR, 2018

Holistic Representations for Memorization and Inference.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Learning Goal-Oriented Visual Dialog via Tempered Policy Gradient.
Proceedings of the 2018 IEEE Spoken Language Technology Workshop, 2018

Efficient Dialog Policy Learning via Positive Memory Retention.
Proceedings of the 2018 IEEE Spoken Language Technology Workshop, 2018

Configuration of Industrial Automation Solutions Using Multi-relational Recommender Systems.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Improving Goal-Oriented Visual Dialog Agents via Advanced Recurrent Nets with Tempered Policy Gradient.
Proceedings of the Linguistic and Cognitive Approaches To Dialog Agents Workshop co-located with the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018), 2018

Improving Information Extraction from Images with Learned Semantic Models.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Explaining Therapy Predictions with Layer-Wise Relevance Propagation in Neural Networks.
Proceedings of the IEEE International Conference on Healthcare Informatics, 2018

Energy-Based Hindsight Experience Prioritization.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Understanding Individual Decisions of CNNs via Contrastive Backpropagation.
Proceedings of the Computer Vision - ACCV 2018, 2018

2017
Tensor Decompositions for Modeling Inverse Dynamics.
CoRR, 2017

The Tensor Memory Hypothesis.
CoRR, 2017

Improving Visual Relationship Detection Using Semantic Modeling of Scene Descriptions.
Proceedings of the Semantic Web - ISWC 2017, 2017

Learning with Knowledge Graphs.
Proceedings of the Twelfth International Workshop on Neural-Symbolic Learning and Reasoning, 2017

Modeling Progression Free Survival in Breast Cancer with Tensorized Recurrent Neural Networks and Accelerated Failure Time Models.
Proceedings of the Machine Learning for Health Care Conference, 2017

Tensor-Train Recurrent Neural Networks for Video Classification.
Proceedings of the 34th International Conference on Machine Learning, 2017

Predictive Modeling of Therapy Decisions in Metastatic Breast Cancer with Recurrent Neural Network Encoder and Multinomial Hierarchical Regression Decoder.
Proceedings of the 2017 IEEE International Conference on Healthcare Informatics, 2017

Embedding Learning for Declarative Memories.
Proceedings of the Semantic Web - 14th International Conference, 2017

Attention-based Information Fusion using Multi-Encoder-Decoder Recurrent Neural Networks.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016
Going Digital: A Survey on Digitalization and Large-Scale Data Analytics in Healthcare.
Proc. IEEE, 2016

A Review of Relational Machine Learning for Knowledge Graphs.
Proc. IEEE, 2016

Big Data: Practical Applications [Scanning the Issue].
Proc. IEEE, 2016

Discovering Similarity and Dissimilarity Relations for Knowledge Propagation in Web Ontologies.
J. Data Semant., 2016

The Clinical Data Intelligence Project - A smart data initiative.
Inform. Spektrum, 2016

Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152).
Dagstuhl Reports, 2016

Predictive Clinical Decision Support System with RNN Encoding and Tensor Decoding.
CoRR, 2016

Relational Models.
CoRR, 2016

Predicting Clinical Events by Combining Static and Dynamic Information Using Recurrent Neural Networks.
CoRR, 2016

Learning representations for discrete sensor networks using tensor decompositions.
Proceedings of the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2016

Predicting Clinical Events by Combining Static and Dynamic Information Using Recurrent Neural Networks.
Proceedings of the 2016 IEEE International Conference on Healthcare Informatics, 2016

Predicting the co-evolution of event and Knowledge Graphs.
Proceedings of the 19th International Conference on Information Fusion, 2016

Embedding Mapping Approaches for Tensor Factorization and Knowledge Graph Modelling.
Proceedings of the Semantic Web. Latest Advances and New Domains, 2016

2015
Exploiting Latent Embeddings of Nominal Clinical Data for Predicting Hospital Readmission.
Künstliche Intell., 2015

Learning with Memory Embeddings.
CoRR, 2015

A Review of Relational Machine Learning for Knowledge Graphs: From Multi-Relational Link Prediction to Automated Knowledge Graph Construction.
CoRR, 2015

Type-Constrained Representation Learning in Knowledge Graphs.
Proceedings of the Semantic Web - ISWC 2015, 2015

Probabilistic Hoeffding Trees - Sped-Up Convergence and Adaption of Online Trees on Changing Data Streams.
Proceedings of the Advances in Data Mining: Applications and Theoretical Aspects, 2015

Predicting Sequences of Clinical Events by Using a Personalized Temporal Latent Embedding Model.
Proceedings of the 2015 International Conference on Healthcare Informatics, 2015

2014
Querying the Web with Statistical Machine Learning.
Proceedings of the Towards the Internet of Services: The THESEUS Research Program, 2014

Core Technologies for the Internet of Services.
Proceedings of the Towards the Internet of Services: The THESEUS Research Program, 2014

Relational Models.
Encyclopedia of Social Network Analysis and Mining, 2014

A scalable approach for statistical learning in semantic graphs.
Semantic Web, 2014

Reality mining on micropost streams - Deductive and inductive reasoning for personalized and location-based recommendations.
Semantic Web, 2014

Learning to Propagate Knowledge in Web Ontologies.
Proceedings of the 10th International Workshop on Uncertainty Reasoning for the Semantic Web (URSW 2014) co-located with the 13th International Semantic Web Conference (ISWC 2014), 2014

Querying Factorized Probabilistic Triple Databases.
Proceedings of the Semantic Web - ISWC 2014, 2014

Probabilistic Latent-Factor Database Models.
Proceedings of the 1st Workshop on Linked Data for Knowledge Discovery co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2014), 2014

Reducing the Rank in Relational Factorization Models by Including Observable Patterns.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Large-scale factorization of type-constrained multi-relational data.
Proceedings of the International Conference on Data Science and Advanced Analytics, 2014

2013
Towards a New Science of a Clinical Data Intelligence.
CoRR, 2013

Logistic Tensor Factorization for Multi-Relational Data.
CoRR, 2013

Tensor Factorization for Multi-relational Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

An Analysis of Tensor Models for Learning on Structured Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Location-Based Mobile Recommendations by Hybrid Reasoning on Social Media Streams.
Proceedings of the Semantic Technology - Third Joint International Conference, 2013

2012
BOTTARI: An augmented reality mobile application to deliver personalized and location-based recommendations by continuous analysis of social media streams.
J. Web Semant., 2012

Context-aware tensor decomposition for relation prediction in social networks.
Soc. Netw. Anal. Min., 2012

Mining the Semantic Web - Statistical learning for next generation knowledge bases.
Data Min. Knowl. Discov., 2012

Deep answers for naturally asked questions on the web of data.
Proceedings of the 21st World Wide Web Conference, 2012

Factorizing YAGO: scalable machine learning for linked data.
Proceedings of the 21st World Wide Web Conference 2012, 2012

Link Prediction in Multi-relational Graphs using Additive Models.
Proceedings of the International Workshop on Semantic Technologies meet Recommender Systems & Big Data, 2012

Scalable Relation Prediction Exploiting Both Intrarelational Correlation and Contextual Information.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Combining Information Extraction, Deductive Reasoning and Machine Learning for Relation Prediction.
Proceedings of the Semantic Web: Research and Applications, 2012

Natural Language Questions for the Web of Data.
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2012

2011
Statistical relational learning of trust.
Mach. Learn., 2011

Semantic Traffic-Aware Routing Using the LarKC Platform.
IEEE Internet Comput., 2011

Making Sense of Location-based Micro-posts Using Stream Reasoning.
Proceedings of the ESWC2011 Workshop on 'Making Sense of Microposts': Big things come in small packages, 2011

A Three-Way Model for Collective Learning on Multi-Relational Data.
Proceedings of the 28th International Conference on Machine Learning, 2011

Graphical Models for Relations - Modeling Relational Context.
Proceedings of the KDIR 2011, 2011

A Novel Metric for Information Retrieval in Semantic Networks.
Proceedings of the Semantic Web: ESWC 2011 Workshops, 2011

Towards BOTTARI: Using Stream Reasoning to Make Sense of Location-Based Micro-posts.
Proceedings of the Semantic Web: ESWC 2011 Workshops, 2011

Modeling and Learning Context-Aware Recommendation Scenarios Using Tensor Decomposition.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2011

2010
Deductive and Inductive Stream Reasoning for Semantic Social Media Analytics.
IEEE Intell. Syst., 2010

Multivariate Prediction for Learning on the Semantic Web.
Proceedings of the Inductive Logic Programming - 20th International Conference, 2010

Digging for knowledge with information extraction: a case study on human gene-disease associations.
Proceedings of the 19th ACM Conference on Information and Knowledge Management, 2010

2009
Statistical Relational Learning with Formal Ontologies.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Multi-Relational Learning with Gaussian Processes.
Proceedings of the IJCAI 2009, 2009

Tutorial summary: Learning with dependencies between several response variables.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Hierarchical Bayesian Models for Collaborative Tagging Systems.
Proceedings of the ICDM 2009, 2009

2008
Extraction of semantic biomedical relations from text using conditional random fields.
BMC Bioinform., 2008

Towards Machine Learning on the Semantic Web.
Proceedings of the Uncertainty Reasoning for the Semantic Web I, 2008

Towards LarKC: A Platform for Web-Scale Reasoning.
Proceedings of the 2th IEEE International Conference on Semantic Computing (ICSC 2008), 2008

Social Network Mining with Nonparametric Relational Models.
Proceedings of the Advances in Social Network Mining and Analysis, 2008

A statistical relational model for trust learning.
Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), 2008

2007
Tailored-to-Fit Bayesian Network Modeling of Expert Diagnostic Knowledge.
J. VLSI Signal Process., 2007

Fast Inference in Infinite Hidden Relational Models.
Proceedings of the Mining and Learning with Graphs, 2007

Robust multi-task learning with <i>t</i>-processes.
Proceedings of the Machine Learning, 2007

Structure Learning with Nonparametric Decomposable Models.
Proceedings of the Artificial Neural Networks, 2007

Learning Initial Trust Among Interacting Agents.
Proceedings of the Cooperative Information Agents XI, 11th International Workshop, 2007

2006
Multi-Output Regularized Feature Projection.
IEEE Trans. Knowl. Data Eng., 2006

Infinite Hidden Relational Models.
Proceedings of the UAI '06, 2006

Stochastic Relational Models for Discriminative Link Prediction.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Supervised probabilistic principal component analysis.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

Collaborative ordinal regression.
Proceedings of the Machine Learning, 2006

Active learning via transductive experimental design.
Proceedings of the Machine Learning, 2006

Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures.
Proceedings of the Machine Learning: ECML 2006, 2006

2005
Multi-label informed latent semantic indexing.
Proceedings of the SIGIR 2005: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2005

A Probabilistic Clustering-Projection Model for Discrete Data.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Soft Clustering on Graphs.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Learning Gaussian processes from multiple tasks.
Proceedings of the Machine Learning, 2005

Dirichlet enhanced relational learning.
Proceedings of the Machine Learning, 2005

Hierarchy-Regularized Latent Semantic Indexing.
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

Multi-Output Regularized Projection.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

2004
Probabilistic Memory-Based Collaborative Filtering.
IEEE Trans. Knowl. Data Eng., 2004

Generative binary codes.
Pattern Anal. Appl., 2004

A nonparametric hierarchical bayesian framework for information filtering.
Proceedings of the SIGIR 2004: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2004

Learning Gaussian Process Kernels via Hierarchical Bayes.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Dirichlet Enhanced Latent Semantic Analysis.
Proceedings of the LWA 2004: Lernen - Wissensentdeckung - Adaptivität, Berlin, 4., 2004

Heterogenous Data Fusion via a Probabilistic Latent-Variable Model.
Proceedings of the Organic and Pervasive Computing, 2004

2003
Classification of rheumatoid joint inflammation based on laser imaging.
IEEE Trans. Biomed. Eng., 2003

Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes.
Proceedings of the UAI '03, 2003

GPPS: A Gaussian Process Positioning System for Cellular Networks.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Knowing a tree from the forest: art image retrieval using a society of profiles.
Proceedings of the Eleventh ACM International Conference on Multimedia, 2003

An Introduction to Nonparametric Hierarchical Bayesian Modelling with a Focus on Multi-agent Learning.
Proceedings of the Switching and Learning in Feedback Systems, 2003

Representative Sampling for Text Classification Using Support Vector Machines.
Proceedings of the Advances in Information Retrieval, 2003

A Hybrid Relevance-Feedback Approach to Text Retrieval.
Proceedings of the Advances in Information Retrieval, 2003

2002
The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Transductive and Inductive Methods for Approximate Gaussian Process Regression.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Removing redundancy and inconsistency in memory-based collaborative filtering.
Proceedings of the 2002 ACM CIKM International Conference on Information and Knowledge Management, 2002

2001
Scaling Kernel-Based Systems to Large Data Sets.
Data Min. Knowl. Discov., 2001

Scalable Kernel Systems.
Proceedings of the Artificial Neural Networks, 2001

The Bayesian Committee Support Vector Machine.
Proceedings of the Artificial Neural Networks, 2001

Knowledge Acquisition and Automated Generation of Bayesian Networks for a Medical Dialogue and Advisory System.
Proceedings of the Artificial Intelligence Medicine, 2001

2000
A Bayesian Committee Machine.
Neural Comput., 2000

Mixtures of Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

The generalized Bayesian committee machine.
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000

A learning vector quantization algorithm for probabilistic models.
Proceedings of the 10th European Signal Processing Conference, 2000

A hidden Markov model for metric and event-based data.
Proceedings of the 10th European Signal Processing Conference, 2000

1999
Neural-network models for the blood glucose metabolism of a diabetic.
IEEE Trans. Neural Networks, 1999

Mixture Approximations to Bayesian Networks.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Robust Neural Network Regression for Offline and Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Mean field inference in a general probabilistic setting.
Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

1998
Averaging, maximum penalized likelihood and Bayesian estimation for improving Gaussian mixture probability density estimates.
IEEE Trans. Neural Networks, 1998

Nonlinear Time-Series Prediction with Missing and Noisy Data.
Neural Comput., 1998

Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Fraud detection in communication networks using neural and probabilistic methods.
Proceedings of the 1998 IEEE International Conference on Acoustics, 1998

1997
Averaging Regularized Estimators.
Neural Comput., 1997

Representing Probabilistic Rules with Networks of Gaussian Basis Functions.
Mach. Learn., 1997

A Solution for Missing Data in Recurrent Neural Networks with an Application to Blood Glucose Prediction.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Nonlinear Markov Networks for Continuous Variables.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Combining Regularized Neural Networks.
Proceedings of the Artificial Neural Networks, 1997

1996
Early Brain Damage.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1995
Die besonderen Eigenschaften Neuronaler Netze bei der Approximation von Funktionen.
Künstliche Intell., 1995

Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Discovering Structure in Continuous Variables Using Bayesian Networks.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

1994
Videographic tomography. II. Reconstruction with fan-beam projection data.
IEEE Trans. Medical Imaging, 1994

Combining Estimators Using Non-Constant Weighting Functions.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Efficient Methods for Dealing with Missing Data in Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

1993
Training Neural Networks with Deficient Data.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Classification with missing and uncertain inputs.
Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993

1992
Network Structuring and Training Using Rule-Based Knowledge.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

Some Solutions to the Missing Feature Problem in Vision.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

Neuronale Netze zur Segmentierung und Clusterung von biomagnetischen Signalen.
Proceedings of the Mustererkennung 1992, 1992

Integrating Rule-Based Knowledge into Neural Computing.
Proceedings of the Mustererkennung 1992, 1992

1991
Incorporating prior knowledge in parsimonious networks of locally tuned units
Forschungsberichte, TU Munich, 1991

Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

A Neural Architecture for 2D and 3D Vision.
Proceedings of the Mustererkennung 1991, 1991

1990
A Neural Network Approach for Three-Dimensional Object Recognition.
Proceedings of the Advances in Neural Information Processing Systems 3, 1990


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