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Found 11 papers, 1 papers with code
Shortcuts for causal discovery of nonlinear models by score matching
The use of simulated data in the field of causal discovery is ubiquitous due to the scarcity of annotated real data.
Scalable Causal Discovery with Score Matching
This paper demonstrates how to discover the whole causal graph from the second derivative of the log-likelihood in observational non-linear additive Gaussian noise models.
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise
Causal discovery methods are intrinsically constrained by the set of assumptions needed to ensure structure identifiability.
Robots with Different Embodiments Can Express and Influence Carefulness in Object Manipulation
Humans have an extraordinary ability to communicate and read the properties of objects by simply watching them being carried by someone else.
Synthesis and Execution of Communicative Robotic Movements with Generative Adversarial Networks
Object manipulation is a natural activity we perform every day.
HHP-Net: A light Heteroscedastic neural network for Head Pose estimation with uncertainty
In this paper we introduce a novel method to estimate the head pose of people in single images starting from a small set of head keypoints.
Property-Aware Robot Object Manipulation: a Generative Approach
When transporting an object, we unconsciously adapt our movement to its properties, for instance by slowing down when the item is fragile.
Action similarity judgment based on kinematic primitives
The results show that both the model and human performance are highly accurate in an action similarity task based on kinematic-level features, which can provide an essential basis for classifying human actions.
The role of ego vision in view-invariant action recognition
Analysis and interpretation of egocentric video data is becoming more and more important with the increasing availability and use of wearable cameras.
Scale Invariant Interest Points with Shearlets
We derive a measure which is very effective for blob detection and closely related to the Laplacian of Gaussian.
Ask the Image: Supervised Pooling to Preserve Feature Locality
In this paper we propose a weighted supervised pooling method for visual recognition systems.
