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 VisionLanguage 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 PreTrained Models for MultiLingual, MultiModal 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 TexttoImage Models using Semantic Guidance.

NIPS/NeurIPS 
2023 
0 
Characteristic Circuits.

NIPS/NeurIPS 
2023 
0 
Rickrolling the Artist: Injecting Backdoors into Text Encoders for TexttoImage 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 NeuralProbabilistic Answer Set Programming.

JAIR 
2023 
0 
Exploiting Cultural Biases via Homoglyphs in TexttoImage Synthesis.

JAIR 
2023 
0 
SumProduct Loop Programming: From Probabilistic Circuits to Loop Programming.

KR 
2022 
0 
NeuralProbabilistic Answer Set Programming.

KR 
2022 
0 
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks.

ICML 
2022 
5 
NeuroSymbolic 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 sumproduct network case.

PGM 
2022 
0 
Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations.

CVPR 
2022 
0 
CLEVACompass: 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 SumProduct Networks: Causal Inference with Tractable Probabilistic Models.

NIPS/NeurIPS 
2021 
14 
Leveraging probabilistic circuits for nonparametric multioutput regression.

UAI 
2021 
6 
Improving AlphaZero Using MonteCarlo 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 NeuroSymbolic Concepts by Interacting With Their Explanations.

CVPR 
2021 
0 
Structure learning for relational logistic regression: an ensemble approach.

DMKD 
2021 
0 
Discriminative NonParametric 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 Dseparation in Abstract Argumentation.

KR 
2020 
0 
CryptoSPN: PrivacyPreserving SumProduct Network Inference.

ECAI 
2020 
8 
Residual SumProduct Networks.

PGM 
2020 
4 
Conditional SumProduct Networks: Imposing Structure on Deep Probabilistic Architectures.

PGM 
2020 
0 
Padé Activation Units: Endtoend Learning of Flexible Activation Functions in Deep Networks.

ICLR 
2020 
0 
Structured ObjectAware 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 AttendInferRepeat with Tractable Probabilistic Models.

ICML 
2019 
40 
Explanatory Interactive Machine Learning.

AIES 
2019 
106 
Random SumProduct Networks: A Simple and Effective Approach to Probabilistic Deep Learning.

UAI 
2019 
69 
Semantics Derived Automatically from Language Corpora Contain Humanlike 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 ContextFree 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 SumProduct Networks: A Deep Architecture for Hybrid Domains.

AAAI 
2018 
79 
SumProduct Autoencoding: Encoding and Decoding Representations Using SumProduct 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 WeisfeilerLehman Graph Kernels: GlobalLocal 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 SumProduct 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 ContinuousTime Bayesian Networks in Relational Domains: A NonParametric Approach.

AAAI 
2016 
15 
Scaling Lifted Probabilistic Inference and Learning Via Graph Databases.

SDM 
2016 
24 
Learning Through AdviceSeeking via Transfer.

ILP 
2016 
1 
Learning Using Unselected Features (LUFe).

IJCAI 
2016 
6 
Propagation kernels: efficient graph kernels from propagated information.

MLJ 
2016 
171 
Gradientbased 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 FreetoPlay 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 kLocality.

AISTATS 
2014 
21 
Mind the Nuisance: Gaussian Process Classification using Privileged Noise.

NIPS/NeurIPS 
2014 
35 
Lifting Relational MAPLPs 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 ReLift: 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 modelbased 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 
PreSymptomatic Prediction of Plant Drought Stress Using DirichletAggregation Regression on Hyperspectral Images.

AAAI 
2012 
21 
Deterministic CUR for Improved LargeScale 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 
Gradientbased 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 
Decisiontheoretic planning with generalized firstorder decision diagrams.

Artificial Intelligence 
2011 
6 
MultiEvidence 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 
Multitask Learning with Task Relations.

ICDM 
2011 
14 
Learning Markov Logic Networks via Functional Gradient Boosting.

ICDM 
2011 
100 
Imitation Learning in Relational Domains: A FunctionalGradient 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 
SelfTaught 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 MessagePassing.

AAAI 
2010 
25 
Symbolic Dynamic Programming for Firstorder POMDPs.

AAAI 
2010 
79 
Topic Models Conditioned on Relations.

ECML/PKDD 
2010 
14 
Fast Active Exploration for LinkBased Preference Learning Using Gaussian Processes.

ECML/PKDD 
2010 
25 
Yes we can: simplex volume maximization for descriptive webscale matrix factorization.

CIKM 
2010 
62 
MultiRelational Learning with Gaussian Processes.

IJCAI 
2009 
58 
Counting Belief Propagation.

UAI 
2009 
170 
ILP, the Blind, and the Elephant: Euclidean Embedding of Coproven 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 Nonnegative 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 
Nonparametric 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 ProofBanks.

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 