Recently, ChatGPT, along with DALL-E-2 and Codex, has been gaining significant attention
from society. As a result, many individuals have become interested in related resources and …

The remarkable performance of deep Convolutional neural networks (CNNs) is generally
attributed to their deeper and wider architectures, which can come with significant …

Many of the existing machine learning algorithms, both supervised and unsupervised,
depend on the quality of the input characteristics to generate a good model. The amount of …

We offer a formal treatment of choice behavior based on the premise that agents minimize
the expected free energy of future outcomes. Crucially, the negative free energy or quality of …

Statistical signal processing applications usually require the estimation of some parameters
of interest given a set of observed data. These estimates are typically obtained either by …

Accurate state of health estimation and end of life prediction is critical for safe and reliable
operation of lithium-ion batteries. This paper proposes a deep Gaussian process algorithm …

This paper presents an empirical study regarding training probabilistic neural networks
using training objectives derived from PAC-Bayes bounds. In the context of probabilistic …

We focus on grounding (ie, localizing or linking) referring expressions in images, eg,``largest
elephant standing behind baby elephant''. This is a general yet challenging vision-language …

In evolutionary biology, niche construction is sometimes described as a genuine
evolutionary process whereby organisms, through their activities and regulatory …

This paper considers goal-directed decision-making in terms of embodied or active
inference. We associate bounded rationality with approximate Bayesian inference that …