SEMI uses multisensory incongruity to self-supervise exploration in reinforcement learning.
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For embodied agents to infer representations of the underlying 3D physical world they inhabit, they should efficiently combine multisensory cues from numerous trials, e.g., by looking at and touching objects. Despite its importance, multisensory 3D scene representation learning has received less attention compared to t…
New logic approach to machine learning prediction.
This paper presents an introduction to the stochastic concepts of \emph{coupling} and \emph{copula}. Coupling means the construction of a joint distribution of two or more random variables that need not be defined on one and the same probability space, whereas a copula is a function that joins a multivariate distributi…
Disagreement between two classifiers regarding the class membership of an observation in pattern recognition can be indicative of an anomaly and its nuance. As in general classifiers base their decision on class aposteriori probabilities, the most natural approach to detecting classifier incongruence is to use divergen…
We improve autoencoder image interpolation by shaping latent space.
Graph neural network improves SOH estimation of lithium-ion batteries.
Humans and animals have the ability to continually acquire, fine-tune, and transfer knowledge and skills throughout their lifespan. This ability, referred to as lifelong learning, is mediated by a rich set of neurocognitive mechanisms that together contribute to the development and specialization of our sensorimotor sk…
Low-cost sensor fusion for organic substance classification.
Study finds discrepancies in open interest reporting for Bitcoin perpetual swaps.
Proposes a new way to represent uncertainty using implied volatility.
MDCN improves treatment effect estimation in multicenter observational studies.