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Universal hydrodynamics of non-conformal branes
We examine the hydrodynamic limit of non-conformal branes using the recently developed precise holographic dictionary. We first streamline the discussion of holography for backgrounds that asymptote
Information-limiting correlations
It is found, analytically and numerically, that decorrelation does not imply an increase in information, and the effect of differential correlations on information can be detected with relatively simple decoders.
Emergent Tool Use From Multi-Agent Autocurricula
This work finds clear evidence of six emergent phases in agent strategy in the authors' environment, each of which creates a new pressure for the opposing team to adapt, and compares hide-and-seek agents to both intrinsic motivation and random initialization baselines in a suite of domain-specific intelligence tests.
Fuzzballs with internal excitations
We construct general 2-charge D1-D5 horizon-free non-singular solutions of IIB supergravity on T4 and K3 describing fuzzballs with excitations in the internal manifold; these excitations are
Precision holography for non-conformal branes
We set up precision holography for the non-conformal branes preserving 16 supersymmetries. The near-horizon limit of all such p-brane solutions with p ? 4, including the case of fundamental string
Correlations and Neuronal Population Information.
It is argued that this is a critical lesson for those interested in neuronal population responses more generally: Descriptions of population responses should be motivated by and linked to well-specified function.
Holographic anatomy of fuzzballs
We present a comprehensive analysis of 2-charge fuzzball solutions, that is, horizon-free non-singular solutions of IIB supergravity characterized by a curve on R4. We propose a precise map that
Origin of information-limiting noise correlations
This study indicates that noise at the sensory periphery could have a major effect on cortical representations in widely studied discrimination tasks and provides an analytical framework to understand the functional relevance of different sources of experimentally measured correlations.
Measuring Fisher Information Accurately in Correlated Neural Populations
There is an alternative, direct estimate of reliability which consistently leads to smaller errors and is much faster to compute and generalizations of the direct estimator are proposed which measure changes in stimulus encoding across conditions and the impact of correlations on encoding and decoding.
Kernel RNN Learning (KeRNL)
We describe Kernel RNN Learning (KeRNL), a reduced-rank, temporal eligibility trace-based approximation to backpropagation through time (BPTT) for training recurrent neural networks (RNNs) that gives