Results 61 to 70 of about 175,776 (260)
Advanced Materials, EarlyView.The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Towards a Law of Invariance in Human Concept Learning [PDF]
, 2011 Invariance principles underlie many key theories in modern science. They provide the explanatory and predictive framework necessary for the rigorous study of natural phenomena ranging from the structure of crystals, to magnetism, to relativistic ...
Vigo, Professor Ronaldo
core
Reproducibility and Natural Exponential Families with Power Variance Functions
The Annals of Statistics, 1986 Let \(X_ 1\),..., \(X_ n\) be independent identically distributed random variables whose common distribution belongs to a family \({\mathcal F}=\{F_{\theta}\in \Theta \subset {\mathbb{R}}\}\) indexed by a parameter \(\theta\). We say that \({\mathcal F}\) is reproducible if there exists a sequence \(\{\) \(\alpha\) (n)\(\}\) such that \[ {\mathcal L ...
Bar-Lev, Shaul K., Enis, Peter
openaire +2 more sources
A Scalable Perovskite Platform With Multi‐State Photoresponsivity for In‐Sensor Saliency Detection
Advanced Materials, EarlyView.A scalable in‐sensor computing platform (32 × 32 array) with ultra‐low variability is developed by incorporating ferroelectric copolymers into halide perovskite thin films. These devices achieve 1000 programmable photoresponsivity states and high thermal reliability.
Xuechao Xing +10 more
wiley +1 more source
Constant Step Size Stochastic Gradient Descent for Probabilistic Modeling [PDF]
, 2018 Stochastic gradient methods enable learning probabilistic models from large amounts of data. While large step-sizes (learning rates) have shown to be best for least-squares (e.g., Gaussian noise) once combined with parameter averaging, these are not ...
Babichev, Dmitry, Bach, Francis
core +2 more sources
Advanced Science, EarlyView.We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich +2 more
wiley +1 more source
Studies on the Marchenko–Pastur Law
MathematicsIn free probability, the theory of Cauchy–Stieltjes Kernel (CSK) families has recently been introduced. This theory is about a set of probability measures defined using the Cauchy kernel similarly to natural exponential families in classical probability ...
Ayed. R. A. Alanzi +3 more
doaj +1 more source
Exponential families, Kahler geometry and quantum mechanics
, 2012 Exponential families are a particular class of statistical manifolds which are particularly important in statistical inference, and which appear very frequently in statistics.
Amari +33 more
core +1 more source
On the Origins of Toughness in Corymbia calophylla (Marri Tree) Nuts
Advanced Science, EarlyView.We uncover the natural toughening mechanisms of the marri nut, including fiber pullout, crack deflection, and a viscoelastic matrix, which enable exceptional energy absorption and ductility comparable to Teflon, with an elastic modulus similar to acrylic.
Wegood M. Awad +7 more
wiley +1 more source
Вестник войск РХБ защитыThe transmission of pathogens from animals to humans is the cause of the appearance of the majority of newly emerging diseases. The purpose of this review is to assess the danger of zoonotic pathogens of dangerous and especially dangerous viral ...
T. E. Sizikova +2 more
doaj +1 more source