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

ICML 
2022 
0 
To Trust or Not To Trust Prediction Scores for Membership Inference Attacks.

IJCAI 
2022 
0 
NeuroSymbolic Verification of Deep Neural Networks.

IJCAI 
2022 
0 
CLEVACompass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability.

ICLR 
2022 
0 
Predictive Whittle networks for time series.

UAI 
2022 
0 
NeuralProbabilistic Answer Set Programming.

KR 
2022 
0 
SumProduct Loop Programming: From Probabilistic Circuits to Loop Programming.

KR 
2022 
0 
Improving AlphaZero Using MonteCarlo Graph Search.

ICAPS 
2021 
0 
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits.

ILP 
2021 
0 
Interventional SumProduct Networks: Causal Inference with Tractable Probabilistic Models.

NIPS/NeurIPS 
2021 
0 
Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions.

AAAI 
2021 
0 
Right for the Right Concept: Revising NeuroSymbolic Concepts by Interacting With Their Explanations.

CVPR 
2021 
0 
Whittle Networks: A Deep Likelihood Model for Time Series.

ICML 
2021 
0 
Leveraging probabilistic circuits for nonparametric multioutput regression.

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

DMKD 
2021 
0 
Discriminative NonParametric Learning of Arithmetic Circuits.

PGM 
2020 
0 
Conditional SumProduct Networks: Imposing Structure on Deep Probabilistic Architectures.

PGM 
2020 
0 
Residual SumProduct Networks.

PGM 
2020 
0 
CryptoSPN: PrivacyPreserving SumProduct Network Inference.

ECAI 
2020 
0 
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits.

ICML 
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 
Independence and Dseparation in Abstract Argumentation.

KR 
2020 
0 
Learning attribute grammars for movement primitive sequencing.

IJRR 
2020 
0 
Explanatory Interactive Machine Learning.

AIES 
2019 
0 
A unifying view of explicit and implicit feature maps of graph kernels.

DMKD 
2019 
0 
Semantics Derived Automatically from Language Corpora Contain Humanlike Moral Choices.

AIES 
2019 
0 
Random SumProduct Networks: A Simple and Effective Approach to Probabilistic Deep Learning.

UAI 
2019 
2 
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs.

AAAI 
2019 
1 
Faster AttendInferRepeat with Tractable Probabilistic Models.

ICML 
2019 
2 
Neural Networks for Relational Data.

ILP 
2019 
0 
Automatic Bayesian Density Analysis.

AAAI 
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 
4 
Efficient Symbolic Integration for Probabilistic Inference.

IJCAI 
2018 
3 
Mixed SumProduct Networks: A Deep Architecture for Hybrid Domains.

AAAI 
2018 
21 
Structure Learning for Relational Logistic Regression: An Ensemble Approach.

KR 
2018 
2 
SumProduct Autoencoding: Encoding and Decoding Representations Using SumProduct Networks.

AAAI 
2018 
9 
Core Dependency Networks.

AAAI 
2018 
3 
Lifted Filtering via Exchangeable Decomposition.

IJCAI 
2018 
2 
Inducing Probabilistic ContextFree Grammars for the Sequencing of Movement Primitives.

ICRA 
2018 
1 
Graph Enhanced Memory Networks for Sentiment Analysis.

ECML/PKDD 
2017 
1 
Stochastic Online Anomaly Analysis for Streaming Time Series.

IJCAI 
2017 
2 
Poisson SumProduct Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions.

AAAI 
2017 
17 
Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach.

ILP 
2017 
4 
Relational linear programming.

Artificial Intelligence 
2017 
12 
Glocalized WeisfeilerLehman Graph Kernels: GlobalLocal Feature Maps of Graphs.

ICDM 
2017 
15 
Lifted Inference for Convex Quadratic Programs.

AAAI 
2017 
4 
The Symbolic Interior Point Method.

AAAI 
2017 
0 
Learning Using Unselected Features (LUFe).

IJCAI 
2016 
2 
Scaling Lifted Probabilistic Inference and Learning Via Graph Databases.

SDM 
2016 
18 
Faster Kernels for Graphs with Continuous Attributes via Hashing.

ICDM 
2016 
18 
Learning ContinuousTime Bayesian Networks in Relational Domains: A NonParametric Approach.

AAAI 
2016 
7 
Learning Through AdviceSeeking via Transfer.

ILP 
2016 
0 
Propagation kernels: efficient graph kernels from propagated information.

MLJ 
2016 
0 
Computer Science on the Move: Inferring Migration Regularities from the Web via Compressed Label Propagation.

IJCAI 
2015 
3 
Transfer Learning via Relational Type Matching.

ICDM 
2015 
9 
Parameterizing the Distance Distribution of Undirected Networks.

UAI 
2015 
4 
Gradientbased boosting for statistical relational learning: the Markov logic network and missing data cases.

MLJ 
2015 
17 
Predicting Purchase Decisions in Mobile FreetoPlay Games.

AIIDE 
2015 
34 
Poisson Dependency Networks: Gradient Boosted Models for Multivariate Count Data.

MLJ 
2015 
19 
pyGPs: a Python library for Gaussian process regression and classification.

JMLR 
2015 
8 
Equitable Partitions of Concave Free Energies.

UAI 
2015 
6 
Power Iterated Color Refinement.

AAAI 
2014 
20 
Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge.

ILP 
2014 
7 
Relational Logistic Regression.

KR 
2014 
31 
Explicit Versus Implicit Graph Feature Maps: A Computational Phase Transition for Walk Kernels.

ICDM 
2014 
16 
Mind the Nuisance: Gaussian Process Classification using Privileged Noise.

NIPS/NeurIPS 
2014 
15 
Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach.

ICDM 
2014 
14 
Efficient Lifting of MAP LP Relaxations Using kLocality.

AISTATS 
2014 
17 
Lifted Message Passing as Reparametrization of Graphical Models.

UAI 
2014 
13 
Lifting Relational MAPLPs Using Cluster Signatures.

AAAI 
2014 
9 
Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels.

ACML 
2013 
5 
Reduce and ReLift: Bootstrapped Lifted Likelihood Maximization for MAP.

AAAI 
2013 
11 
Accelerating Imitation Learning in Relational Domains via Transfer by Initialization.

ILP 
2013 
6 
Exploiting symmetries for scaling loopy belief propagation and relational training.

MLJ 
2013 
46 
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 
PreSymptomatic Prediction of Plant Drought Stress Using DirichletAggregation Regression on Hyperspectral Images.

AAAI 
2012 
11 
Matrix Factorization as Search.

ECML/PKDD 
2012 
3 
Efficient Graph Kernels by Randomization.

ECML/PKDD 
2012 
40 
Efficient Learning for Hashing Proportional Data.

ICDM 
2012 
3 
Deterministic CUR for Improved LargeScale Data Analysis: An Empirical Study.

SDM 
2012 
8 
Lifted Linear Programming.

AISTATS 
2012 
36 
Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data.

AISTATS 
2012 
7 
Lifted Probabilistic Inference.

ECAI 
2012 
70 
Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants.

UAI 
2012 
4 
Simplex Distributions for Embedding Data Matrices over Time.

SDM 
2012 
9 
Symbolic Dynamic Programming for Continuous State and Observation POMDPs.

NIPS/NeurIPS 
2012 
9 
Lifted Online Training of Relational Models with Stochastic Gradient Methods.

ECML/PKDD 
2012 
20 
Exploration in relational domains for modelbased reinforcement learning.

JMLR 
2012 
35 
Pairwise Markov Logic.

ILP 
2012 
5 
Descriptive matrix factorization for sustainability Adopting the principle of opposites.

DMKD 
2012 
0 
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 
15 
MultiEvidence Lifted Message Passing, with Application to PageRank and the Kalman Filter.

IJCAI 
2011 
27 
Learning Markov Logic Networks via Functional Gradient Boosting.

ICDM 
2011 
65 
Imitation Learning in Relational Domains: A FunctionalGradient Boosting Approach.

IJCAI 
2011 
40 
More influence means less work: fast latent dirichlet allocation by influence scheduling.

CIKM 
2011 
7 
Multitask Learning with Task Relations.

ICDM 
2011 
5 
Decisiontheoretic planning with generalized firstorder decision diagrams.

Artificial Intelligence 
2011 
5 
Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation.

AAAI 
2011 
11 
Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning.

MLJ 
2011 
0 
Learning to hash logistic regression for fast 3D scan point classification.

IROS 
2010 
17 
Fast Active Exploration for LinkBased Preference Learning Using Gaussian Processes.

ECML/PKDD 
2010 
19 
Informed Lifting for MessagePassing.

AAAI 
2010 
23 
Hierarchical Convex NMF for Clustering Massive Data.

ACML 
2010 
19 
SelfTaught Decision Theoretic Planning with First Order Decision Diagrams.

ICAPS 
2010 
19 
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.

ECML/PKDD 
2010 
16 
Topic Models Conditioned on Relations.

ECML/PKDD 
2010 
9 
Exploration in Relational Worlds.

ECML/PKDD 
2010 
16 
Yes we can: simplex volume maximization for descriptive webscale matrix factorization.

CIKM 
2010 
47 
Symbolic Dynamic Programming for Firstorder POMDPs.

AAAI 
2010 
49 
Counting Belief Propagation.

UAI 
2009 
137 
MultiRelational Learning with Gaussian Processes.

IJCAI 
2009 
45 
Kernel Conditional Quantile Estimation via Reduction Revisited.

ICDM 
2009 
22 
Convex Nonnegative Matrix Factorization in the Wild.

ICDM 
2009 
47 
Stacked Gaussian Process Learning.

ICDM 
2009 
24 
Generalized First Order Decision Diagrams for First Order Markov Decision Processes.

IJCAI 
2009 
16 
Learning Preferences with Hidden Common Cause Relations.

ECML/PKDD 
2009 
12 
ILP, the Blind, and the Elephant: Euclidean Embedding of Coproven Queries.

ILP 
2009 
2 
Lifted Probabilistic Inference with Counting Formulas.

AAAI 
2008 
159 
Learning predictive terrain models for legged robot locomotion.

IROS 
2008 
46 
Logical Hierarchical Hidden Markov Models for Modeling User Activities.

ILP 
2008 
36 
Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness.

ECML/PKDD 
2008 
45 
Parameter Learning in Probabilistic Databases: A Least Squares Approach.

ECML/PKDD 
2008 
43 
Nonparametric policy gradients: a unified treatment of propositional and relational domains.

ICML 
2008 
50 
SRL without Tears: An ILP Perspective.

ILP 
2008 
0 
Boosting Relational Sequence Alignments.

ICDM 
2008 
20 
Compressing probabilistic Prolog programs.

MLJ 
2008 
0 
Integrating Naïve Bayes and FOIL.

JMLR 
2007 
41 
Most likely heteroscedastic Gaussian process regression.

ICML 
2007 
157 
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders.

RSS 
2007 
44 
Relational Sequence Alignments and Logos.

ILP 
2006 
8 
TildeCRF: Conditional Random Fields for Logical Sequences.

ECML/PKDD 
2006 
49 
Logical Hidden Markov Models.

JAIR 
2006 
75 
Revising Probabilistic Prolog Programs.

ILP 
2006 
1 
Learning Relational Navigation Policies.

IROS 
2006 
0 
Robust 3D Scan Point Classification using Associative Markov Networks.

ICRA 
2006 
68 
Fisher Kernels for Relational Data.

ECML/PKDD 
2006 
8 
nFOIL: Integrating Naïve Bayes and FOIL.

AAAI 
2005 
61 
Towards Learning Stochastic Logic Programs from ProofBanks.

AAAI 
2005 
11 
"Say EM" for Selecting Probabilistic Models for Logical Sequences.

UAI 
2005 
0 
Bellman goes relational.

ICML 
2004 
70 
Fisher Kernels for Logical Sequences.

ECML/PKDD 
2004 
15 
Logical Markov Decision Programs and the Convergence of Logical TD(lambda).

ILP 
2004 
24 
Balios  The Engine for Bayesian Logic Programs.

ECML/PKDD 
2004 
5 
Scaled CGEM: A Fast Accelerated EM.

ECML/PKDD 
2003 
5 
Towards Combining Inductive Logic Programming with Bayesian Networks.

ILP 
2001 
102 
Adaptive Bayesian Logic Programs.

ILP 
2001 
43 