1.7k citations · 2.4k across the 47 of their papers we have counts for
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Does Your Model Think Like an Engineer? Explainable AI for Bearing Fault Detection with Deep Learning
Thomas Decker, Michael Lebacher, Volker Tresp
Deep Learning has already been successfully applied to analyze industrial sensor data in a variety of relevant use cases. However, the opaque nature of many well-performing methods…
Categorical EHR Imputation with Generative Adversarial Nets
Yinchong Yang, Zhiliang Wu, Volker Tresp +1
Electronic Health Records often suffer from missing data, which poses a major problem in clinical practice and clinical studies. A novel approach for dealing with missing data are…
Few-Shot One-Class Classification via Meta-Learning
Ahmed Frikha, Denis Krompaß, Hans-Georg Köpken +1
Although few-shot learning and one-class classification (OCC), i.e., learning a binary classifier with data from only one class, have been separately well studied, their intersecti…
Graph Hawkes Neural Network for Forecasting on Temporal Knowledge Graphs
Zhen Han, Yunpu Ma, Yuyi Wang +2
The Hawkes process has become a standard method for modeling self-exciting event sequences with different event types. A recent work has generalized the Hawkes process to a neurall…
Mutual Information-based State-Control for Intrinsically Motivated Reinforcement Learning
Rui Zhao, Yang Gao, Pieter Abbeel +2
In reinforcement learning, an agent learns to reach a set of goals by means of an external reward signal. In the natural world, intelligent organisms learn from internal drives, by…
Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs
Marcel Hildebrandt, Jorge Andres Quintero Serna, Yunpu Ma +3
We propose a novel method for fact-checking on knowledge graphs based on debate dynamics. The underlying idea is to frame the task of triple classification as a debate game between…