Suchergebnis | Hamburg Open Science

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22 Einträge gefunden

Neural Field Conditioning Strategies for 2D Semantic Segmentation
2023 - Forschungsinformationssystem der UHH - frei zugänglich
A Closer Look at Reward Decomposition for High-Level Robotic Explanations
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
Curriculum goal masking for continuous deep reinforcement learning
2019 - TUHH Open Research
Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue
2018 - Forschungsinformationssystem der UHH
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
The next generation of robots
1. Magg, Sven
2. Wermter, Stefan
2018 - Forschungsinformationssystem der UHH
A Context-based Approach for Dialogue Act Recognition using Simple Recurrent Neural Networks
2018 - Forschungsinformationssystem der UHH - frei zugänglich
Improving interactive reinforcement learning:What makes a good teacher?
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
Attention modeled as information in learning multisensory integration
2015 - Forschungsinformationssystem der UHH - frei zugänglich
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

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Neural Field Conditioning Strategies for 2D Semantic Segmentation

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

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

Curriculum goal masking for continuous deep reinforcement learning

Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue

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

The next generation of robots

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

Improving interactive reinforcement learning:What makes a good teacher?

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

Attention modeled as information in learning multisensory integration

Learning human motion feedback with neural self-organization

Analysing the multiple timescale recurrent neural network for embodied language understanding