Search Results for author:
Found 6 papers, 2 papers with code
Estimating Q(s,s') with Deterministic Dynamics Gradients
In this paper, we introduce a novel form of a value function, $Q(s, s')$, that expresses the utility of transitioning from a state $s$ to a neighboring state $s'$ and then acting optimally thereafter.
T-HITL Effectively Addresses Problematic Associations in Image Generation and Maintains Overall Visual Quality
Building on sociological literature (Blumer, 1958) and mapping representations to model behaviors, we have developed a taxonomy to study problematic associations in image generation models.
End-to-end Material Thermal Conductivity Prediction through Machine Learning
We assessed the performance of state-of-the-art machine learning models for thermal conductivity prediction on this expanded dataset and observed that all these models suffered from overfitting.
Modelling Social Context for Fake News Detection: A Graph Neural Network Based Approach
This paper has analyzed the social context of fake news detection with a hybrid graph neural network based approach.
Estimating Q(s,s') with Deep Deterministic Dynamics Gradients
In this paper, we introduce a novel form of value function, $Q(s, s')$, that expresses the utility of transitioning from a state $s$ to a neighboring state $s'$ and then acting optimally thereafter.
Meta-Graph: Few Shot Link Prediction via Meta Learning
We consider the task of few shot link prediction on graphs.
