97 citations · 239 across the 26 of their papers we have counts for
27 papers
Towards Learning a Generalizable 3D Scene Representation from 2D Observations
Martin Gromniak, Jan-Gerrit Habekost, Sebastian Kamp +2
We introduce a Generalizable Neural Radiance Field approach for predicting 3D workspace occupancy from egocentric robot observations. Unlike prior methods operating in camera-centr…
Causal State Distillation for Explainable Reinforcement Learning
Wenhao Lu, Xufeng Zhao, Thilo Fryen +4
Reinforcement learning (RL) is a powerful technique for training intelligent agents, but understanding why these agents make specific decisions can be quite challenging. This lack…
Neural Field Conditioning Strategies for 2D Semantic Segmentation
Martin Gromniak, Sven Magg, Stefan Wermter
Neural fields are neural networks which map coordinates to a desired signal. When a neural field should jointly model multiple signals, and not memorize only one, it needs to be co…
A Closer Look at Reward Decomposition for High-Level Robotic Explanations
Wenhao Lu, Xufeng Zhao, Sven Magg +3
Explaining the behaviour of intelligent agents learned by reinforcement learning (RL) to humans is challenging yet crucial due to their incomprehensible proprioceptive states, vari…
A Sub-Layered Hierarchical Pyramidal Neural Architecture for Facial Expression Recognition
Henrique Siqueira, Pablo Barros, Sven Magg +2
In domains where computational resources and labeled data are limited, such as in robotics, deep networks with millions of weights might not be the optimal solution. In this paper,…
Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE)
A. Sutherland, S. Bensch, T. Hellström +2
Sentiment analysis has transitioned from classifying the sentiment of an entire sentence to providing the contextual information of what targets exist in a sentence, what sentiment…