Results 91 to 100 of about 1,514,883 (344)

Asymptotic latent solitons, black strings and black branes in f(R)-gravity

open access: yes, 2011
We investigate nonlinear f(R) theories in the Kaluza-Klein models with toroidal compactification of extra dimensions. A point-like matter source has the dust-like equation of state in our three dimensions and nonzero equations of state in the extra ...
A. De Felice   +4 more
core   +1 more source

Interactions between Molten High‐Silicon Electrical Steels and Carbon‐Bonded MgO Refractories Based on Recyclates

open access: yesAdvanced Engineering Materials, EarlyView.
This study examines how several molten high‐silicon electrical steels interact with both conventional and recycled MgO–C refractories. For this, various immersion experiments are conducted. In addition to infiltration, a number of mechanisms are identified and explained that control the corrosion of the refractory material.
Lukas Neubert   +7 more
wiley   +1 more source

Bayesian Inference for Latent Biologic Structure with Determinantal Point Processes (DPP)

open access: yes, 2015
We discuss the use of the determinantal point process (DPP) as a prior for latent structure in biomedical applications, where inference often centers on the interpretation of latent features as biologically or clinically meaningful structure.
Mueller, Peter   +2 more
core   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

open access: yesAdvanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone   +11 more
wiley   +1 more source

Tensor decompositions for learning latent variable models [PDF]

open access: yes, 2014
This work considers a computationally and statistically efficient parameter estimation method for a wide class of latent variable models---including Gaussian mixture models, hidden Markov models, and latent Dirichlet allocation---which exploits a certain
Anandkumar, Anima   +4 more
core   +5 more sources

Host‐Directed Biomaterials for Combatting Bloodstream Infections: From Macrocyclic Peptides to Immune‐Activating Cell Backpacks

open access: yesAdvanced Functional Materials, EarlyView.
Bloodstream infections (BSI) are one of the leading causes of mortality and morbidity in both civilian and military populations. This paper summarizes recent progress in novel treatment strategies to manage BSI arising from both bacterial and fungal pathogens using molecules, particles, and materials to elicit host‐directed immunity.
Thomas Thomou   +11 more
wiley   +1 more source

Are there different phenotypes of thoracic surgery patients? A latent class analysis of pretreatment patient-reported outcomesCentral MessagePerspective

open access: yesJTCVS Open
Background: Among patients undergoing thoracic surgery, quality of life is associated with multiple perioperative outcomes. Whether patients suffer reduced quality of life in certain areas compared to others is unclear.
Eagan J. Peters, MD   +5 more
doaj   +1 more source

Dynamic Control of Synaptic Plasticity by Competing Ferroelectric and Trap‐Assisted Switching in IGZO Transistors with Al2O3/HfO2 Dielectrics

open access: yesAdvanced Functional Materials, EarlyView.
A frequency‐tunable ferroelectric synaptic transistor based on a buried‐gate InGaZnO channel and Al2O3/HfO2 dielectric stack exhibits linear and reversible weight updates using single‐polarity pulses. By switching between ferroelectric and trap‐assisted modes depending on input frequency, the device simplifies neuromorphic circuit design and achieves ...
Ojun Kwon   +8 more
wiley   +1 more source

Deep Exponential Families [PDF]

open access: yes, 2014
We describe \textit{deep exponential families} (DEFs), a class of latent variable models that are inspired by the hidden structures used in deep neural networks.
Blei, David M.   +3 more
core   +1 more source

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