Publications (31)
On the Conditional Independence Implication Problem: A Lattice-Theoretic Approach
Mathias Niepert, Dirk Van Gucht, Marc Gyssens
Learning Sequence Encoders for Temporal Knowledge Graph Completion
Alberto GarcÃa-Durán, Sebastijan DumanÄiÄ, Mathias Niepert
Net2Vec: Deep Learning for the Network
Roberto Gonzalez, Filipe Manco, Alberto Garcia-Duran +4
Learning Convolutional Neural Networks for Graphs
Mathias Niepert, Mohamed Ahmed, Konstantin Kutzkov
Tractability through Exchangeability: A New Perspective on Efficient Probabilistic Inference
Mathias Niepert, Guy Van den Broeck
Lifted Probabilistic Inference for Asymmetric Graphical Models
Guy Van den Broeck, Mathias Niepert
Markov Chains on Orbits of Permutation Groups
Mathias Niepert
Learning Short-Cut Connections for Object Counting
Daniel Oñoro-Rubio, Mathias Niepert, Roberto J. López-Sastre
Logical Inference Algorithms and Matrix Representations for Probabilistic Conditional Independence
Mathias Niepert
LODE: Linking Digital Humanities Content to the Web of Data
Jakob Huber, Timo Sztyler, Jan Noessner +3
MMKG: Multi-Modal Knowledge Graphs
Ye Liu, Hui Li, Alberto Garcia-Duran +3
Contextual Hourglass Networks for Segmentation and Density Estimation
Daniel Oñoro-Rubio, Mathias Niepert
Learning Graph Representations with Embedding Propagation
Alberto Garcia-Duran, Mathias Niepert
Towards a Spectrum of Graph Convolutional Networks
Mathias Niepert, Alberto Garcia-Duran
A Delayed Column Generation Strategy for Exact k-Bounded MAP Inference in Markov Logic Networks
Mathias Niepert
Symmetry-Aware Marginal Density Estimation
Mathias Niepert
Learning Representations of Missing Data for Predicting Patient Outcomes
Brandon Malone, Alberto Garcia-Duran, Mathias Niepert
Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
Daniel Oñoro-Rubio, Mathias Niepert, Alberto GarcÃa-Durán +2
KBLRN : End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features
Alberto Garcia-Duran, Mathias Niepert
LRMM: Learning to Recommend with Missing Modalities
Cheng Wang, Mathias Niepert, Hui Li
Markov Chains on Orbits of Permutation Groups
Mathias Niepert
Representation Learning for Resource Usage Prediction
Florian Schmidt, Mathias Niepert, Felipe Huici
State-Regularized Recurrent Neural Networks
Cheng Wang, Mathias Niepert
RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems
Cheng Wang, Mathias Niepert, Hui Li
TransRev: Modeling Reviews as Translations from Users to Items
Alberto Garcia-Duran, Roberto Gonzalez, Daniel Onoro-Rubio +2
BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism
Nicolas Weber, Florian Schmidt, Mathias Niepert +1
Discriminative Gaifman Models
Mathias Niepert
On the Conditional Independence Implication Problem: A Lattice-Theoretic Approach
Mathias Niepert, Dirk Van Gucht, Marc Gyssens
Exchangeable Variable Models
Mathias Niepert, Pedro Domingos
Knowledge Graph Completion to Predict Polypharmacy Side Effects
Brandon Malone, Alberto GarcÃa-Durán, Mathias Niepert
RockIt: Exploiting Parallelism and Symmetry for MAP Inference in Statistical Relational Models
Jan Noessner, Mathias Niepert, Heiner Stuckenschmidt