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21 Einträge gefunden

A Closer Look at Reward Decomposition for High-Level Robotic Explanations
2023 - Forschungsinformationssystem der UHH - frei zugänglich
Neural Field Conditioning Strategies for 2D Semantic Segmentation
2023 - Forschungsinformationssystem der UHH - frei zugänglich
Hierarchical goals contextualize local reward decomposition explanations
2022 - Forschungsinformationssystem der UHH - frei zugänglich
EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural Annotators
2020 - Forschungsinformationssystem der UHH - frei zugänglich
Incorporating end-to-end speech recognition models for sentiment analysis
2019 - Forschungsinformationssystem der UHH
The next generation of robots
1. Magg, Sven
2. Wermter, Stefan
2018 - Forschungsinformationssystem der UHH
Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue
2018 - Forschungsinformationssystem der UHH
Improving interactive reinforcement learning:What makes a good teacher?
2018 - Forschungsinformationssystem der UHH - frei zugänglich
Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks
2018 - Forschungsinformationssystem der UHH - frei zugänglich
Deep reinforcement learning using compositional representations for performing instructions
2018 - Forschungsinformationssystem der UHH - frei zugänglich
EmoRL: Continuous acoustic emotion classification using deep reinforcement learning
2018 - Forschungsinformationssystem der UHH
A Context-based Approach for Dialogue Act Recognition using Simple Recurrent Neural Networks
2018 - Forschungsinformationssystem der UHH - frei zugänglich
Agent-advising Approaches in an Interactive Reinforcement Learning Scenario
2017 - Forschungsinformationssystem der UHH
Human motion assessment in real time using recurrent self-organization
2016 - Forschungsinformationssystem der UHH - frei zugänglich
Training agents with interactive reinforcement learning and contextual affordances
2016 - Forschungsinformationssystem der UHH - frei zugänglich
Towards Effective Classification of Imbalanced Data With Convolutional Neural Networks
2016 - Forschungsinformationssystem der UHH
Learning human motion feedback with neural self-organization
2015 - Forschungsinformationssystem der UHH
Analysing the multiple timescale recurrent neural network for embodied language understanding
2015 - Forschungsinformationssystem der UHH
Attention modeled as information in learning multisensory integration
2015 - Forschungsinformationssystem der UHH - frei zugänglich
Improving reinforcement learning with interactive feedback and affordances
2014 - Forschungsinformationssystem der UHH

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A Closer Look at Reward Decomposition for High-Level Robotic Explanations

Neural Field Conditioning Strategies for 2D Semantic Segmentation

Hierarchical goals contextualize local reward decomposition explanations

EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural Annotators

Incorporating end-to-end speech recognition models for sentiment analysis

The next generation of robots

Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue

Improving interactive reinforcement learning:What makes a good teacher?

Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks

Deep reinforcement learning using compositional representations for performing instructions

EmoRL: Continuous acoustic emotion classification using deep reinforcement learning

A Context-based Approach for Dialogue Act Recognition using Simple Recurrent Neural Networks

Agent-advising Approaches in an Interactive Reinforcement Learning Scenario

Human motion assessment in real time using recurrent self-organization

Training agents with interactive reinforcement learning and contextual affordances

Towards Effective Classification of Imbalanced Data With Convolutional Neural Networks

Learning human motion feedback with neural self-organization

Analysing the multiple timescale recurrent neural network for embodied language understanding

Attention modeled as information in learning multisensory integration

Improving reinforcement learning with interactive feedback and affordances