… [45], the billions of mobile devices running DNN inference, and the rapid growth of AI chips,…
used in DNN inference. Rather than executing all the required mathematical operations with …

… further mathematical details below. Finally, note that Bayesian inference in cognition is …
to believe that elicited priors are not a perfect representation of a user’s prior beliefs, we find …

… under active inference are metabolically efficient and suggest that neural representations
in … brain, but also yield useful insights into mathematical optimisation and machine learning. …

… representations are mathematical, rather than cognitive, and a fictionalist or instrumentalist
account, according to which representations … -energy principle and active inference, we argue …

… infer the development of particular internal representation … the origins of embodied
representation lie in the movement of … cognition theory and representation theory in mathematics …

… from the computational procedures of arithmetic, even though … We limited our examples to
arithmetic for several reasons. … planning inferences do deal with the object representation. …

… local discourse level processes (ie, constructing accurate representations of sentences, and
… were significant predictors of elaborative inferences and performance on the traditional and …

… performance and efficiency, mainly focusing on inference [4], [5], training [6] of DNNs, and
exploiting low- and tunable-precision arithmetic to … -dimensional holistic representations of the …

… HDC during the inference, ie, 83% average performance for all … In this paper, we exploit the
mathematical orthogonality of … store P hypervectors as binary representation and use them as …

… and requires less time for training and inference [9]. These features are a result of its ultra-wide
data representation and underlying mathematical operations. One thing that should be …