1.7k citations · 2.4k across the 47 of their papers we have counts for
10 papers · 1 filter
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…
Relation Transformer Network
Rajat Koner, Suprosanna Shit, Volker Tresp
The extraction of a scene graph with objects as nodes and mutual relationships as edges is the basis for a deep understanding of image content. Despite recent advances, such as mes…
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…
The Tensor Brain: Semantic Decoding for Perception and Memory
Volker Tresp, Sahand Sharifzadeh, Dario Konopatzki +1
We analyse perception and memory, using mathematical models for knowledge graphs and tensors, to gain insights into the corresponding functionalities of the human mind. Our discuss…
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…
Search for Better Students to Learn Distilled Knowledge
Jindong Gu, Volker Tresp
Knowledge Distillation, as a model compression technique, has received great attention. The knowledge of a well-performed teacher is distilled to a student with a small architectur…