Sep 20, 2020 · The prediction function is used as a forward model for search on a graph in a viewpoint-matching task and the representation learned to maximize ...
We introduce a new way of learning this representation along with the prediction function, a system we dub Latent Representation Prediction Network (LARP).
Jun 8, 2024 · This method learns state representations by predicting the representation of the environment's next state given a current state and action. The ...
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Sep 20, 2020 · A new way of jointly learning this representation along with the prediction function is proposed, which is used as a forward model for ...
Mar 3, 2021 · First, neural networks are able to extract latent semantic characteristics from linguistic corpora when trained to predict the context in which ...
Our aim is to allow agents to form mental models of their environments for planning. Building on insights gained from knowledge distillation methods.
Apr 9, 2024 · We take the use case of continuous field reconstruction using implicit neural networks for climate science and report the findings as a work in progress.
This paper explores use of Capsule Networks (CapsNets) in the context of learning a hierarchical representation of sparse semantic layers.
We propose a framework for the completely unsupervised learning of latent object properties from their interactions: the perception-prediction network (PPN) ...
To incorporate geographical influence, we propose a novel latent representation model, called POI2Vec. ... Whats your next move: User activity prediction in ...