18 citations · 51 across the 22 of their papers we have counts for
6 papers · 1 filter
NMINE: Normalized Mutual Information Neural Estimation
Petra Eerikinharju, Marko Tuononen, Ville Hautamäki
Mutual information is a general measure of statistical dependence that captures both linear and nonlinear relationships between random variables. For continuous and multidimensiona…
Zero-Shot Heart Rate Variability Forecasting from Consumer Wearables Using Time Series Foundation Models
Luukas Peräkylä, Fahad Sohrab, Ville Hautamäki +3
Short-term Heart Rate Variability (HRV) forecasting could provide clinicians with actionable lead time for detecting autonomic dysfunction and adverse cardiac events. Consumer wear…
Behavioral Cloning via Search in Video PreTraining Latent Space
Federico Malato, Florian Leopold, Amogh Raut +2
Our aim is to build autonomous agents that can solve tasks in environments like Minecraft. To do so, we used an imitation learning-based approach. We formulate our control problem…
VoxCeleb Enrichment for Age and Gender Recognition
Khaled Hechmi, Trung Ngo Trong, Ville Hautamaki +1
VoxCeleb datasets are widely used in speaker recognition studies. Our work serves two purposes. First, we provide speaker age labels and (an alternative) annotation of speaker gend…
Do Autonomous Agents Benefit from Hearing?
Abraham Woubie, Anssi Kanervisto, Janne Karttunen +1
Mapping states to actions in deep reinforcement learning is mainly based on visual information. The commonly used approach for dealing with visual information is to extract pixels…
From Video Game to Real Robot: The Transfer between Action Spaces
Janne Karttunen, Anssi Kanervisto, Ville Kyrki +1
Deep reinforcement learning has proven to be successful for learning tasks in simulated environments, but applying same techniques for robots in real-world domain is more challengi…