Kristian Kersting
207 publications
34 venues
H Index 41
Affiliation
TU Darmstadt, Computer Science Department, GermanyTU 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
Links
DBLPGoogle Scholar
Twitter- https://ml-research.github.io/people/kkersting/
- http://www.ml.informatik.tu-darmstadt.de/#bio
- http://www-ai.cs.uni-dortmund.de/PERSONAL/kersting.html
- http://people.csail.mit.edu/kersting/
- https://openreview.net/profile?id=~Kristian_Kersting1
- https://en.wikipedia.org/wiki/Kristian_Kersting
- https://orcid.org/0000-0002-2873-9152
- https://www.wikidata.org/entity/Q72740096
- https://id.loc.gov/authorities/names/no2007046979
- https://d-nb.info/gnd/173912001
| Name | Venue | Year | citations |
|---|---|---|---|
Judging Quality Across Languages: A Multilingual Approach to Pretraining Data Filtering with Language Models.
|
EMNLP | 2025 | 0 |
| Scaling Probabilistic Circuits via Data Partitioning.
|
UAI | 2025 | 0 |
| ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding.
|
ICLR | 2025 | 3 |
| Multilingual Text-to-Image Generation Magnifies Gender Stereotypes.
|
ACL | 2025 | 5 |
| METok: Multi-Stage Event-based Token Compression for Efficient Long Video Understanding.
|
EMNLP | 2025 | 3 |
| Human-in-the-loop or AI-in-the-loop? Automate or Collaborate?
|
AAAI | 2025 | 0 |
| Bongard in Wonderland: Visual Puzzles that Still Make AI Go Mad?
|
ICML | 2025 | 0 |
| LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models.
|
ICML | 2025 | 0 |
| Where is the Truth? The Risk of Getting Confounded in a Continual World.
|
ICML | 2025 | 0 |
| Right on Time: Revising Time Series Models by Constraining Their Explanations.
|
ECML/PKDD | 2025 | 0 |
| STRICTA: Structured Reasoning in Critical Text Assessment for Peer Review and Beyond.
|
ACL | 2025 | 0 |
| Credibility-Aware Multimodal Fusion Using Probabilistic Circuits.
|
AISTATS | 2025 | 0 |
| BlendRL: A Framework for Merging Symbolic and Neural Policy Learning.
|
ICLR | 2025 | 0 |
| Systems with Switching Causal Relations: A Meta-Causal Perspective.
|
ICLR | 2025 | 0 |
| The Constitutional Filter: Bayesian Estimation of Compliant Agents.
|
IROS | 2025 | 0 |
| Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents.
|
NIPS/NeurIPS | 2024 | 25 |
| DeiSAM: Segment Anything with Deictic Prompting.
|
NIPS/NeurIPS | 2024 | 6 |
| Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models.
|
NIPS/NeurIPS | 2024 | 32 |
| Mechanistic Design and Scaling of Hybrid Architectures.
|
ICML | 2024 | 53 |
| Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG.
|
ICLR | 2024 | 9 |
| Neural Concept Binder.
|
NIPS/NeurIPS | 2024 | 14 |
| Chain Versus Common Cause: Biased Causal Strength Judgments in Humans and Large Language Models.
|
Cognitive Science | 2024 | 4 |
| Exploiting Cultural Biases via Homoglyphs inText-to-Image Synthesis (Abstract Reprint).
|
IJCAI | 2024 | 1 |
| Graph Neural Networks Need Cluster-Normalize-Activate Modules.
|
NIPS/NeurIPS | 2024 | 5 |
| Pix2Code: Learning to Compose Neural Visual Concepts as Programs.
|
UAI | 2024 | 21 |
| Ψnet: Efficient Causal Modeling at Scale.
|
PGM | 2024 | 3 |
| χSPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains.
|
UAI | 2024 | 3 |
| T-FREE: Subword Tokenizer-Free Generative LLMs via Sparse Representations for Memory-Efficient Embeddings.
|
EMNLP | 2024 | 9 |
| Learning to Intervene on Concept Bottlenecks.
|
ICML | 2024 | 0 |
| Deep Classifier Mimicry without Data Access.
|
AISTATS | 2024 | 0 |
| LEDITS++: Limitless Image Editing Using Text-to-Image Models.
|
CVPR | 2024 | 0 |
| Defending Our Privacy with Backdoors.
|
ECAI | 2024 | 0 |
| Representation Matters for Mastering Chess: Improved Feature Representation in AlphaZero Outperforms Switching to Transformers.
|
ECAI | 2024 | 0 |
| Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks.
|
ICLR | 2024 | 0 |
| Adaptive Rational Activations to Boost Deep Reinforcement Learning.
|
ICLR | 2024 | 0 |
| Learning differentiable logic programs for abstract visual reasoning.
|
MLJ | 2024 | 0 |
| Structural causal models reveal confounder bias in linear program modelling.
|
MLJ | 2024 | 0 |
| Does CLIP Know My Face?
|
JAIR | 2024 | 0 |
| SEGA: Instructing Text-to-Image Models using Semantic Guidance.
|
NIPS/NeurIPS | 2023 | 0 |
| Scalable Neural-Probabilistic Answer Set Programming.
|
JAIR | 2023 | 20 |
| Probabilistic circuits that know what they don't know.
|
UAI | 2023 | 11 |
| Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction.
|
NIPS/NeurIPS | 2023 | 54 |
| Vision Relation Transformer for Unbiased Scene Graph Generation.
|
ICCV | 2023 | 26 |
| Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference.
|
UAI | 2023 | 16 |
| Characteristic Circuits.
|
NIPS/NeurIPS | 2023 | 9 |
| Do Not Marginalize Mechanisms, Rather Consolidate!
|
NIPS/NeurIPS | 2023 | 1 |
| ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation.
|
NIPS/NeurIPS | 2023 | 37 |
| MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation.
|
NIPS/NeurIPS | 2023 | 28 |
| ILLUME: Rationalizing Vision-Language Models through Human Interactions.
|
ICML | 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 |
| Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis.
|
ICCV | 2023 | 0 |
| αILP: thinking visual scenes as differentiable logic programs.
|
MLJ | 2023 | 0 |
| Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis.
|
JAIR | 2023 | 0 |
| Predictive Whittle networks for time series.
|
UAI | 2022 | 4 |
| Neural-Probabilistic Answer Set Programming.
|
KR | 2022 | 20 |
| Neuro-Symbolic Verification of Deep Neural Networks.
|
IJCAI | 2022 | 23 |
| Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks.
|
ICML | 2022 | 85 |
| Sum-Product Loop Programming: From Probabilistic Circuits to Loop Programming.
|
KR | 2022 | 4 |
| 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 | 2 |
| Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions.
|
AAAI | 2021 | 45 |
| Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models.
|
NIPS/NeurIPS | 2021 | 39 |
| Whittle Networks: A Deep Likelihood Model for Time Series.
|
ICML | 2021 | 16 |
| Improving AlphaZero Using Monte-Carlo Graph Search.
|
ICAPS | 2021 | 19 |
| Leveraging probabilistic circuits for nonparametric multi-output regression.
|
UAI | 2021 | 16 |
| 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 |
| CryptoSPN: Privacy-Preserving Sum-Product Network Inference.
|
ECAI | 2020 | 11 |
| Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits.
|
ICML | 2020 | 151 |
| Discriminative Non-Parametric Learning of Arithmetic Circuits.
|
PGM | 2020 | 1 |
| Independence and D-separation in Abstract Argumentation.
|
KR | 2020 | 4 |
| Residual Sum-Product Networks.
|
PGM | 2020 | 9 |
| 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 |
| Learning attribute grammars for movement primitive sequencing.
|
IJRR | 2020 | 0 |
| Neural Networks for Relational Data.
|
ILP | 2019 | 8 |
| Faster Attend-Infer-Repeat with Tractable Probabilistic Models.
|
ICML | 2019 | 59 |
| Semantics Derived Automatically from Language Corpora Contain Human-like Moral Choices.
|
AIES | 2019 | 71 |
| Explanatory Interactive Machine Learning.
|
AIES | 2019 | 249 |
| Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs.
|
AAAI | 2019 | 14 |
| Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning.
|
UAI | 2019 | 130 |
| 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 |
| Lifted Filtering via Exchangeable Decomposition.
|
IJCAI | 2018 | 8 |
| Systems AI: A Declarative Learning Based Programming Perspective.
|
IJCAI | 2018 | 12 |
| Core Dependency Networks.
|
AAAI | 2018 | 19 |
| Structure Learning for Relational Logistic Regression: An Ensemble Approach.
|
KR | 2018 | 12 |
| Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives.
|
ICRA | 2018 | 6 |
| Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks.
|
AAAI | 2018 | 30 |
| Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains.
|
AAAI | 2018 | 107 |
| Efficient Symbolic Integration for Probabilistic Inference.
|
IJCAI | 2018 | 0 |
| Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach.
|
ILP | 2017 | 19 |
| Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions.
|
AAAI | 2017 | 34 |
| Relational linear programming.
|
Artificial Intelligence | 2017 | 22 |
| Graph Enhanced Memory Networks for Sentiment Analysis.
|
ECML/PKDD | 2017 | 1 |
| Glocalized Weisfeiler-Lehman Graph Kernels: Global-Local Feature Maps of Graphs.
|
ICDM | 2017 | 91 |
| Lifted Inference for Convex Quadratic Programs.
|
AAAI | 2017 | 7 |
| Stochastic Online Anomaly Analysis for Streaming Time Series.
|
IJCAI | 2017 | 21 |
| The Symbolic Interior Point Method.
|
AAAI | 2017 | 0 |
| Learning Through Advice-Seeking via Transfer.
|
ILP | 2016 | 2 |
| Faster Kernels for Graphs with Continuous Attributes via Hashing.
|
ICDM | 2016 | 105 |
| Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach.
|
AAAI | 2016 | 16 |
| Scaling Lifted Probabilistic Inference and Learning Via Graph Databases.
|
SDM | 2016 | 23 |
| Learning Using Unselected Features (LUFe).
|
IJCAI | 2016 | 6 |
| Propagation kernels: efficient graph kernels from propagated information.
|
MLJ | 2016 | 0 |
| Parameterizing the Distance Distribution of Undirected Networks.
|
UAI | 2015 | 6 |
| pyGPs: a Python library for Gaussian process regression and classification.
|
JMLR | 2015 | 29 |
| Predicting Purchase Decisions in Mobile Free-to-Play Games.
|
AIIDE | 2015 | 99 |
| Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases.
|
MLJ | 2015 | 4 |
| Equitable Partitions of Concave Free Energies.
|
UAI | 2015 | 7 |
| Computer Science on the Move: Inferring Migration Regularities from the Web via Compressed Label Propagation.
|
IJCAI | 2015 | 8 |
| Transfer Learning via Relational Type Matching.
|
ICDM | 2015 | 38 |
| Poisson Dependency Networks: Gradient Boosted Models for Multivariate Count Data.
|
MLJ | 2015 | 2 |
| Efficient Lifting of MAP LP Relaxations Using k-Locality.
|
AISTATS | 2014 | 21 |
| Power Iterated Color Refinement.
|
AAAI | 2014 | 39 |
| Mind the Nuisance: Gaussian Process Classification using Privileged Noise.
|
NIPS/NeurIPS | 2014 | 41 |
| Lifting Relational MAP-LPs Using Cluster Signatures.
|
AAAI | 2014 | 16 |
| Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach.
|
ICDM | 2014 | 30 |
| Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge.
|
ILP | 2014 | 11 |
| Lifted Message Passing as Reparametrization of Graphical Models.
|
UAI | 2014 | 14 |
| Explicit Versus Implicit Graph Feature Maps: A Computational Phase Transition for Walk Kernels.
|
ICDM | 2014 | 28 |
| Relational Logistic Regression.
|
KR | 2014 | 0 |
| Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels.
|
ACML | 2013 | 6 |
| Exploiting symmetries for scaling loopy belief propagation and relational training.
|
MLJ | 2013 | 2 |
| Accelerating Imitation Learning in Relational Domains via Transfer by Initialization.
|
ILP | 2013 | 8 |
| Reduce and Re-Lift: Bootstrapped Lifted Likelihood Maximization for MAP.
|
AAAI | 2013 | 12 |
| 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 |
| Efficient Learning for Hashing Proportional Data.
|
ICDM | 2012 | 4 |
| Pairwise Markov Logic.
|
ILP | 2012 | 5 |
| Lifted Probabilistic Inference.
|
ECAI | 2012 | 122 |
| Exploration in relational domains for model-based reinforcement learning.
|
JMLR | 2012 | 64 |
| Descriptive matrix factorization for sustainability Adopting the principle of opposites.
|
DMKD | 2012 | 72 |
| Simplex Distributions for Embedding Data Matrices over Time.
|
SDM | 2012 | 18 |
| Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data.
|
AISTATS | 2012 | 11 |
| Lifted Online Training of Relational Models with Stochastic Gradient Methods.
|
ECML/PKDD | 2012 | 24 |
| Matrix Factorization as Search.
|
ECML/PKDD | 2012 | 3 |
| Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images.
|
AAAI | 2012 | 26 |
| Efficient Graph Kernels by Randomization.
|
ECML/PKDD | 2012 | 65 |
| Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study.
|
SDM | 2012 | 25 |
| Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants.
|
UAI | 2012 | 7 |
| Lifted Linear Programming.
|
AISTATS | 2012 | 48 |
| Symbolic Dynamic Programming for Continuous State and Observation POMDPs.
|
NIPS/NeurIPS | 2012 | 15 |
| Gradient-based boosting for statistical relational learning: The relational dependency network case.
|
MLJ | 2012 | 0 |
| Decision-theoretic planning with generalized first-order decision diagrams.
|
Artificial Intelligence | 2011 | 9 |
| Multi-task Learning with Task Relations.
|
ICDM | 2011 | 17 |
| Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation.
|
AAAI | 2011 | 15 |
| Learning Markov Logic Networks via Functional Gradient Boosting.
|
ICDM | 2011 | 107 |
| Larger Residuals, Less Work: Active Document Scheduling for Latent Dirichlet Allocation.
|
ECML/PKDD | 2011 | 20 |
| More influence means less work: fast latent dirichlet allocation by influence scheduling.
|
CIKM | 2011 | 8 |
| Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach.
|
IJCAI | 2011 | 0 |
| Multi-Evidence Lifted Message Passing, with Application to PageRank and the Kalman Filter.
|
IJCAI | 2011 | 0 |
| Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning.
|
MLJ | 2011 | 0 |
| Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.
|
ECML/PKDD | 2010 | 18 |
| Exploration in Relational Worlds.
|
ECML/PKDD | 2010 | 17 |
| Symbolic Dynamic Programming for First-order POMDPs.
|
AAAI | 2010 | 94 |
| Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes.
|
ECML/PKDD | 2010 | 24 |
| Informed Lifting for Message-Passing.
|
AAAI | 2010 | 24 |
| Topic Models Conditioned on Relations.
|
ECML/PKDD | 2010 | 16 |
| Yes we can: simplex volume maximization for descriptive web-scale matrix factorization.
|
CIKM | 2010 | 61 |
| Self-Taught Decision Theoretic Planning with First Order Decision Diagrams.
|
ICAPS | 2010 | 22 |
| Hierarchical Convex NMF for Clustering Massive Data.
|
ACML | 2010 | 34 |
| Learning to hash logistic regression for fast 3D scan point classification.
|
IROS | 2010 | 21 |
| Learning Preferences with Hidden Common Cause Relations.
|
ECML/PKDD | 2009 | 18 |
| Stacked Gaussian Process Learning.
|
ICDM | 2009 | 43 |
| 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 | 23 |
| Counting Belief Propagation.
|
UAI | 2009 | 179 |
| Kernel Conditional Quantile Estimation via Reduction Revisited.
|
ICDM | 2009 | 40 |
| Convex Non-negative Matrix Factorization in the Wild.
|
ICDM | 2009 | 70 |
| Multi-Relational Learning with Gaussian Processes.
|
IJCAI | 2009 | 59 |
| Lifted Probabilistic Inference with Counting Formulas.
|
AAAI | 2008 | 231 |
| Non-parametric policy gradients: a unified treatment of propositional and relational domains.
|
ICML | 2008 | 75 |
| Boosting Relational Sequence Alignments.
|
ICDM | 2008 | 24 |
| Compressing probabilistic Prolog programs.
|
MLJ | 2008 | 44 |
| Parameter Learning in Probabilistic Databases: A Least Squares Approach.
|
ECML/PKDD | 2008 | 73 |
| Logical Hierarchical Hidden Markov Models for Modeling User Activities.
|
ILP | 2008 | 46 |
| Learning predictive terrain models for legged robot locomotion.
|
IROS | 2008 | 93 |
| Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness.
|
ECML/PKDD | 2008 | 108 |
| SRL without Tears: An ILP Perspective.
|
ILP | 2008 | 1 |
| Integrating Naïve Bayes and FOIL.
|
JMLR | 2007 | 72 |
| Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders.
|
RSS | 2007 | 54 |
| Most likely heteroscedastic Gaussian process regression.
|
ICML | 2007 | 400 |
| Robust 3D Scan Point Classification using Associative Markov Networks.
|
ICRA | 2006 | 100 |
| Fisher Kernels for Relational Data.
|
ECML/PKDD | 2006 | 11 |
| Learning Relational Navigation Policies.
|
IROS | 2006 | 36 |
| TildeCRF: Conditional Random Fields for Logical Sequences.
|
ECML/PKDD | 2006 | 71 |
| 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 | 26 |
| Towards Learning Stochastic Logic Programs from Proof-Banks.
|
AAAI | 2005 | 16 |
| nFOIL: Integrating Naïve Bayes and FOIL.
|
AAAI | 2005 | 104 |
| Balios - The Engine for Bayesian Logic Programs.
|
ECML/PKDD | 2004 | 17 |
| Fisher Kernels for Logical Sequences.
|
ECML/PKDD | 2004 | 21 |
| Logical Markov Decision Programs and the Convergence of Logical TD(lambda).
|
ILP | 2004 | 33 |
| Bellman goes relational.
|
ICML | 2004 | 123 |
| Scaled CGEM: A Fast Accelerated EM.
|
ECML/PKDD | 2003 | 11 |
| Adaptive Bayesian Logic Programs.
|
ILP | 2001 | 122 |
| Towards Combining Inductive Logic Programming with Bayesian Networks.
|
ILP | 2001 | 161 |