Name Venue Year citations
Structured Object-Aware Physics Prediction for Video Modeling and Planning. ICLR 2020 0
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks. ICLR 2020 0
CryptoSPN: Privacy-Preserving Sum-Product Network Inference. ECAI 2020 0
Independence and D-separation 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 Human-like Moral Choices. AIES 2019 0
Random Sum-Product 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 Attend-Infer-Repeat with Tractable Probabilistic Models. ICML 2019 2
Automatic Bayesian Density Analysis. AAAI 2019 0
Neural Networks for Relational Data. ILP 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 Sum-Product Networks: A Deep Architecture for Hybrid Domains. AAAI 2018 21
Structure Learning for Relational Logistic Regression: An Ensemble Approach. KR 2018 2
Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks. AAAI 2018 9
Core Dependency Networks. AAAI 2018 3
Lifted Filtering via Exchangeable Decomposition. IJCAI 2018 2
Inducing Probabilistic Context-Free 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 Sum-Product 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 Weisfeiler-Lehman Graph Kernels: Global-Local 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 Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach. AAAI 2016 7
Learning Through Advice-Seeking 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
Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases. MLJ 2015 17
Predicting Purchase Decisions in Mobile Free-to-Play 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 k-Locality. AISTATS 2014 17
Lifted Message Passing as Reparametrization of Graphical Models. UAI 2014 13
Lifting Relational MAP-LPs 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 Re-Lift: 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. MLJ 2013 0
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. DMKD 2013 0
Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation 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 Large-Scale 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 model-based reinforcement learning. JMLR 2012 35
Pairwise Markov Logic. ILP 2012 5
Gradient-based boosting for statistical relational learning: The relational dependency network case. MLJ 2012 0
Descriptive matrix factorization for sustainability Adopting the principle of opposites. DMKD 2012 0
Larger Residuals, Less Work: Active Document Scheduling for Latent Dirichlet Allocation. ECML/PKDD 2011 15
Multi-Evidence 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 Functional-Gradient Boosting Approach. IJCAI 2011 40
More influence means less work: fast latent dirichlet allocation by influence scheduling. CIKM 2011 7
Multi-task Learning with Task Relations. ICDM 2011 5
Decision-theoretic planning with generalized first-order 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 Link-Based Preference Learning Using Gaussian Processes. ECML/PKDD 2010 19
Informed Lifting for Message-Passing. AAAI 2010 23
Hierarchical Convex NMF for Clustering Massive Data. ACML 2010 19
Self-Taught 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 web-scale matrix factorization. CIKM 2010 47
Symbolic Dynamic Programming for First-order POMDPs. AAAI 2010 49
Counting Belief Propagation. UAI 2009 137
Multi-Relational Learning with Gaussian Processes. IJCAI 2009 45
Kernel Conditional Quantile Estimation via Reduction Revisited. ICDM 2009 22
Convex Non-negative 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 Co-proven 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
Non-parametric 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 Proof-Banks. 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
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