Kristian Kersting

170 publications

31 venues

H Index 39


TU Darmstadt, Computer Science Department, Germany
TU Darmstadt, Centre for Cognitive Science, Germany
TU Dortmund, Department of Computer Science, Germany
University of Bonn, Faculty of Agriculture, Germany
Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Sankt Augustin, Germany
Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory (CSAIL), Cambridge, MA, USA
University of Freiburg, Machine Learning Laborator, Germany


Name Venue Year citations
Structural causal models reveal confounder bias in linear program modelling. MLJ 2024 0
Probabilistic circuits that know what they don't know. UAI 2023 0
ILLUME: Rationalizing Vision-Language Models through Human Interactions. ICML 2023 0
Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference. UAI 2023 0
Boosting Object Representation Learning via Motion and Object Continuity. ECML/PKDD 2023 0
Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models. CVPR 2023 0
Revision Transformers: Instructing Language Models to Change Their Values. ECAI 2023 0
Do Not Marginalize Mechanisms, Rather Consolidate! NIPS/NeurIPS 2023 0
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation. NIPS/NeurIPS 2023 0
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction. NIPS/NeurIPS 2023 0
ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation. NIPS/NeurIPS 2023 0
SEGA: Instructing Text-to-Image Models using Semantic Guidance. NIPS/NeurIPS 2023 0
Characteristic Circuits. NIPS/NeurIPS 2023 0
Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis. ICCV 2023 0
Vision Relation Transformer for Unbiased Scene Graph Generation. ICCV 2023 0
αILP: thinking visual scenes as differentiable logic programs. MLJ 2023 0
Scalable Neural-Probabilistic Answer Set Programming. JAIR 2023 0
Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis. JAIR 2023 0
Sum-Product Loop Programming: From Probabilistic Circuits to Loop Programming. KR 2022 0
Neural-Probabilistic Answer Set Programming. KR 2022 0
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks. ICML 2022 5
Neuro-Symbolic Verification of Deep Neural Networks. IJCAI 2022 3
Predictive Whittle networks for time series. UAI 2022 1
To Trust or Not To Trust Prediction Scores for Membership Inference Attacks. IJCAI 2022 0
Explaining Deep Tractable Probabilistic Models: The sum-product network case. PGM 2022 0
Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations. CVPR 2022 0
CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability. ICLR 2022 0
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits. ILP 2021 0
Whittle Networks: A Deep Likelihood Model for Time Series. ICML 2021 8
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. NIPS/NeurIPS 2021 14
Leveraging probabilistic circuits for nonparametric multi-output regression. UAI 2021 6
Improving AlphaZero Using Monte-Carlo Graph Search. ICAPS 2021 1
Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions. AAAI 2021 18
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations. CVPR 2021 0
Structure learning for relational logistic regression: an ensemble approach. DMKD 2021 0
Discriminative Non-Parametric Learning of Arithmetic Circuits. PGM 2020 1
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. ICML 2020 56
Learning attribute grammars for movement primitive sequencing. IJRR 2020 7
Independence and D-separation in Abstract Argumentation. KR 2020 0
CryptoSPN: Privacy-Preserving Sum-Product Network Inference. ECAI 2020 8
Residual Sum-Product Networks. PGM 2020 4
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. PGM 2020 0
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks. ICLR 2020 0
Structured Object-Aware Physics Prediction for Video Modeling and Planning. ICLR 2020 0
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs. AAAI 2019 13
Neural Networks for Relational Data. ILP 2019 6
Faster Attend-Infer-Repeat with Tractable Probabilistic Models. ICML 2019 40
Explanatory Interactive Machine Learning. AIES 2019 106
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. UAI 2019 69
Semantics Derived Automatically from Language Corpora Contain Human-like Moral Choices. AIES 2019 36
Automatic Bayesian Density Analysis. AAAI 2019 0
A unifying view of explicit and implicit feature maps of graph kernels. DMKD 2019 0
Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach. Autonomous Robots 2019 0
Systems AI: A Declarative Learning Based Programming Perspective. IJCAI 2018 11
Lifted Filtering via Exchangeable Decomposition. IJCAI 2018 8
Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives. ICRA 2018 4
Efficient Symbolic Integration for Probabilistic Inference. IJCAI 2018 24
Structure Learning for Relational Logistic Regression: An Ensemble Approach. KR 2018 9
Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains. AAAI 2018 79
Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks. AAAI 2018 23
Core Dependency Networks. AAAI 2018 15
Lifted Inference for Convex Quadratic Programs. AAAI 2017 4
Graph Enhanced Memory Networks for Sentiment Analysis. ECML/PKDD 2017 1
Glocalized Weisfeiler-Lehman Graph Kernels: Global-Local Feature Maps of Graphs. ICDM 2017 64
Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach. ILP 2017 17
Relational linear programming. Artificial Intelligence 2017 17
Stochastic Online Anomaly Analysis for Streaming Time Series. IJCAI 2017 18
Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions. AAAI 2017 30
The Symbolic Interior Point Method. AAAI 2017 0
Faster Kernels for Graphs with Continuous Attributes via Hashing. ICDM 2016 2
Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach. AAAI 2016 15
Scaling Lifted Probabilistic Inference and Learning Via Graph Databases. SDM 2016 24
Learning Through Advice-Seeking via Transfer. ILP 2016 1
Learning Using Unselected Features (LUFe). IJCAI 2016 6
Propagation kernels: efficient graph kernels from propagated information. MLJ 2016 171
Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases. MLJ 2015 34
Poisson Dependency Networks: Gradient Boosted Models for Multivariate Count Data. MLJ 2015 0
Predicting Purchase Decisions in Mobile Free-to-Play Games. AIIDE 2015 81
Equitable Partitions of Concave Free Energies. UAI 2015 7
pyGPs: a Python library for Gaussian process regression and classification. JMLR 2015 21
Parameterizing the Distance Distribution of Undirected Networks. UAI 2015 5
Computer Science on the Move: Inferring Migration Regularities from the Web via Compressed Label Propagation. IJCAI 2015 7
Transfer Learning via Relational Type Matching. ICDM 2015 32
Efficient Lifting of MAP LP Relaxations Using k-Locality. AISTATS 2014 21
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. NIPS/NeurIPS 2014 35
Lifting Relational MAP-LPs Using Cluster Signatures. AAAI 2014 15
Relational Logistic Regression. KR 2014 52
Lifted Message Passing as Reparametrization of Graphical Models. UAI 2014 14
Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach. ICDM 2014 23
Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge. ILP 2014 9
Power Iterated Color Refinement. AAAI 2014 38
Explicit Versus Implicit Graph Feature Maps: A Computational Phase Transition for Walk Kernels. ICDM 2014 28
Exploiting symmetries for scaling loopy belief propagation and relational training. MLJ 2013 78
Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels. ACML 2013 7
Reduce and Re-Lift: Bootstrapped Lifted Likelihood Maximization for MAP. AAAI 2013 12
Accelerating Imitation Learning in Relational Domains via Transfer by Initialization. ILP 2013 6
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. DMKD 2013 0
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. MLJ 2013 0
Symbolic Dynamic Programming for Continuous State and Observation POMDPs. NIPS/NeurIPS 2012 12
Lifted Probabilistic Inference. ECAI 2012 115
Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants. UAI 2012 7
Exploration in relational domains for model-based reinforcement learning. JMLR 2012 0
Efficient Graph Kernels by Randomization. ECML/PKDD 2012 64
Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data. AISTATS 2012 9
Lifted Online Training of Relational Models with Stochastic Gradient Methods. ECML/PKDD 2012 24
Pairwise Markov Logic. ILP 2012 5
Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images. AAAI 2012 21
Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study. SDM 2012 23
Simplex Distributions for Embedding Data Matrices over Time. SDM 2012 16
Descriptive matrix factorization for sustainability Adopting the principle of opposites. DMKD 2012 68
Lifted Linear Programming. AISTATS 2012 47
Matrix Factorization as Search. ECML/PKDD 2012 3
Efficient Learning for Hashing Proportional Data. ICDM 2012 4
Gradient-based boosting for statistical relational learning: The relational dependency network case. MLJ 2012 0
Larger Residuals, Less Work: Active Document Scheduling for Latent Dirichlet Allocation. ECML/PKDD 2011 20
Decision-theoretic planning with generalized first-order decision diagrams. Artificial Intelligence 2011 6
Multi-Evidence Lifted Message Passing, with Application to PageRank and the Kalman Filter. IJCAI 2011 34
More influence means less work: fast latent dirichlet allocation by influence scheduling. CIKM 2011 8
Multi-task Learning with Task Relations. ICDM 2011 14
Learning Markov Logic Networks via Functional Gradient Boosting. ICDM 2011 100
Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach. IJCAI 2011 62
Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation. AAAI 2011 15
Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning. MLJ 2011 0
Self-Taught Decision Theoretic Planning with First Order Decision Diagrams. ICAPS 2010 21
Learning to hash logistic regression for fast 3D scan point classification. IROS 2010 21
Exploration in Relational Worlds. ECML/PKDD 2010 17
Hierarchical Convex NMF for Clustering Massive Data. ACML 2010 31
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. ECML/PKDD 2010 18
Informed Lifting for Message-Passing. AAAI 2010 25
Symbolic Dynamic Programming for First-order POMDPs. AAAI 2010 79
Topic Models Conditioned on Relations. ECML/PKDD 2010 14
Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes. ECML/PKDD 2010 25
Yes we can: simplex volume maximization for descriptive web-scale matrix factorization. CIKM 2010 62
Multi-Relational Learning with Gaussian Processes. IJCAI 2009 58
Counting Belief Propagation. UAI 2009 170
ILP, the Blind, and the Elephant: Euclidean Embedding of Co-proven Queries. ILP 2009 3
Generalized First Order Decision Diagrams for First Order Markov Decision Processes. IJCAI 2009 22
Learning Preferences with Hidden Common Cause Relations. ECML/PKDD 2009 17
Convex Non-negative Matrix Factorization in the Wild. ICDM 2009 66
Stacked Gaussian Process Learning. ICDM 2009 42
Kernel Conditional Quantile Estimation via Reduction Revisited. ICDM 2009 34
Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness. ECML/PKDD 2008 99
Parameter Learning in Probabilistic Databases: A Least Squares Approach. ECML/PKDD 2008 66
Lifted Probabilistic Inference with Counting Formulas. AAAI 2008 219
SRL without Tears: An ILP Perspective. ILP 2008 1
Logical Hierarchical Hidden Markov Models for Modeling User Activities. ILP 2008 47
Compressing probabilistic Prolog programs. MLJ 2008 41
Learning predictive terrain models for legged robot locomotion. IROS 2008 85
Boosting Relational Sequence Alignments. ICDM 2008 25
Non-parametric policy gradients: a unified treatment of propositional and relational domains. ICML 2008 71
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders. RSS 2007 55
Integrating Naïve Bayes and FOIL. JMLR 2007 70
Most likely heteroscedastic Gaussian process regression. ICML 2007 328
Learning Relational Navigation Policies. IROS 2006 40
Robust 3D Scan Point Classification using Associative Markov Networks. ICRA 2006 95
Fisher Kernels for Relational Data. ECML/PKDD 2006 11
TildeCRF: Conditional Random Fields for Logical Sequences. ECML/PKDD 2006 70
Revising Probabilistic Prolog Programs. ILP 2006 0
Relational Sequence Alignments and Logos. ILP 2006 0
Logical Hidden Markov Models. JAIR 2006 0
"Say EM" for Selecting Probabilistic Models for Logical Sequences. UAI 2005 27
Towards Learning Stochastic Logic Programs from Proof-Banks. AAAI 2005 15
nFOIL: Integrating Naïve Bayes and FOIL. AAAI 2005 101
Logical Markov Decision Programs and the Convergence of Logical TD(lambda). ILP 2004 36
Fisher Kernels for Logical Sequences. ECML/PKDD 2004 21
Balios - The Engine for Bayesian Logic Programs. ECML/PKDD 2004 17
Bellman goes relational. ICML 2004 121
Scaled CGEM: A Fast Accelerated EM. ECML/PKDD 2003 10
Adaptive Bayesian Logic Programs. ILP 2001 119
Towards Combining Inductive Logic Programming with Bayesian Networks. ILP 2001 158
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