Search Results - "Struckmeier, Oliver"

Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding by Pearson, Martin J, Dora, Shirin, Struckmeier, Oliver, Knowles, Thomas C, Mitchinson, Ben, Tiwari, Kshitij, Kyrki, Ville, Bohte, Sander, Pennartz, Cyriel M A

“…Recognising familiar places is a competence required in many engineering applications that interact with the real world such as robot navigation. Combining…”
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Autoencoding slow representations for semi-supervised data-efficient regression by Struckmeier, Oliver, Tiwari, Kshitij, Kyrki, Ville

“…The slowness principle is a concept inspired by the visual cortex of the brain. It postulates that the underlying generative factors of a quickly varying…”
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Domain Curiosity: Learning Efficient Data Collection Strategies for Domain Adaptation by Arndt, Karol, Struckmeier, Oliver, Kyrki, Ville

“…Domain adaptation is a common problem in robotics, with applications such as transferring policies from simulation to real world and lifelong learning…”
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Autonomous Generation of Robust and Focused Explanations for Robot Policies by Struckmeier, Oliver, Racca, Mattia, Kyrki, Ville

“…Transparency of robot behaviors increases efficiency and quality of interactions with humans. To increase transparency of robot policies, we propose a method…”
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LeagueAI: Improving object detector performance and flexibility through automatically generated training data and domain randomization by Struckmeier, Oliver

“…In this technical report I present my method for automatic synthetic dataset generation for object detection and demonstrate it on the video game League of…”
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Domain Curiosity: Learning Efficient Data Collection Strategies for Domain Adaptation by Arndt, Karol, Struckmeier, Oliver, Kyrki, Ville

“…Domain adaptation is a common problem in robotics, with applications such as transferring policies from simulation to real world and lifelong learning…”
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Autoencoding Slow Representations for Semi-supervised Data Efficient Regression by Struckmeier, Oliver, Tiwari, Kshitij, Kyrki, Ville

“…The slowness principle is a concept inspired by the visual cortex of the brain. It postulates that the underlying generative factors of a quickly varying…”
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Learning representations that are closed-form Monge mapping optimal with application to domain adaptation by Struckmeier, Oliver, Redko, Ievgen, Mallasto, Anton, Arndt, Karol, Heinonen, Markus, Kyrki, Ville

“…Optimal transport (OT) is a powerful geometric tool used to compare and align probability measures following the least effort principle. Despite its widespread…”
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From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport by Bouniot, Quentin, Redko, Ievgen, Mallasto, Anton, Laclau, Charlotte, Arndt, Karol, Struckmeier, Oliver, Heinonen, Markus, Kyrki, Ville, Kaski, Samuel

“…In the last decade, we have witnessed the introduction of several novel deep neural network (DNN) architectures exhibiting ever-increasing performance across…”
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ViTa-SLAM: A Bio-inspired Visuo-Tactile SLAM for Navigation while Interacting with Aliased Environments by Struckmeier, Oliver, Tiwari, Kshitij, Salman, Mohammed, Pearson, Martin J., Kyrki, Ville

“…RatSLAM is a rat hippocampus-inspired visual Simultaneous Localization and Mapping (SLAM) framework capable of generating semi-metric topological…”
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ViTa-SLAM: Biologically-Inspired Visuo-Tactile SLAM by Struckmeier, Oliver, Tiwari, Kshitij, Pearson, Martin J, Kyrki, Ville

“…In this work, we propose a novel, bio-inspired multi-sensory SLAM approach called ViTa-SLAM. Compared to other multisensory SLAM variants, this approach allows…”
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ViTa-SLAM: A Bio-inspired Visuo-Tactile SLAM for Navigation while Interacting with Aliased Environments by Struckmeier, Oliver, Tiwari, Kshitij, Salman, Mohammed, Pearson, Martin J, Kyrki, Ville

“…RatSLAM is a rat hippocampus-inspired visual Simultaneous Localization and Mapping (SLAM) framework capable of generating semi-metric topological…”
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MuPNet: Multi-modal Predictive Coding Network for Place Recognition by Unsupervised Learning of Joint Visuo-Tactile Latent Representations by Struckmeier, Oliver, Tiwari, Kshitij, Dora, Shirin, Pearson, Martin J, Bohte, Sander M, Pennartz, Cyriel MA, Kyrki, Ville

“…Extracting and binding salient information from different sensory modalities to determine common features in the environment is a significant challenge in…”
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