Search Results for author:
Found 9 papers, 0 papers with code
Conformance checking: A state-of-the-art literature review
Conformance checking is a set of process mining functions that compare process instances with a given process model.
Analyzing Customer Feedback for Product Fit Prediction
One of the biggest hurdles for customers when purchasing fashion online, is the difficulty of finding products with the right fit.
Improving Visual Relationship Detection using Semantic Modeling of Scene Descriptions
In this paper we consider scene descriptions which are represented as a set of triples (subject, predicate, object), where each triple consists of a pair of visual objects, which appear in the image, and the relationship between them (e. g. man-riding-elephant, man-wearing-hat).
Improving Information Extraction from Images with Learned Semantic Models
Many applications require an understanding of an image that goes beyond the simple detection and classification of its objects.
Attention-based Information Fusion using Multi-Encoder-Decoder Recurrent Neural Networks
With the rising number of interconnected devices and sensors, modeling distributed sensor networks is of increasing interest.
Tensor Decompositions for Modeling Inverse Dynamics
The decomposition of sparse tensors has successfully been used in relational learning, e. g., the modeling of large knowledge graphs.
Predicting the Co-Evolution of Event and Knowledge Graphs
By predicting future events, we also predict likely changes in the knowledge graph and thus obtain a model for the evolution of the knowledge graph as well.
Learning with Memory Embeddings
We introduce a number of hypotheses on human memory that can be derived from the developed mathematical models.
Type-Constrained Representation Learning in Knowledge Graphs
Latent variable models have increasingly gained attention for the statistical modeling of knowledge graphs, showing promising results in tasks related to knowledge graph completion and cleaning.
