Results 11 to 20 of about 25,214,365 (363)
Variational Elliptical Processes
CoRR, 2023 We present elliptical processes, a family of non-parametric probabilistic models that subsume Gaussian processes and Student's t processes. This generalization includes a range of new heavy-tailed behaviors while retaining computational tractability. Elliptical processes are based on a representation of elliptical distributions as a continuous mixture ...
Bånkestad, Maria +3 more
openaire +4 more sources
Variational Gaussian Process Diffusion Processes
CoRR, 2023 International Conference on Artificial Intelligence and Statistics (AISTATS ...
Prakhar Verma, Vincent Adam, Arno Solin
openaire +4 more sources
Deep Variational Implicit Processes
CoRR, 2022 Implicit processes (IPs) are a generalization of Gaussian processes (GPs). IPs may lack a closed-form expression but are easy to sample from. Examples include, among others, Bayesian neural networks or neural samplers. IPs can be used as priors over functions, resulting in flexible models with well-calibrated prediction uncertainty estimates.
Luis A. Ortega 0001 +2 more
openaire +3 more sources
Ultra-Low Power Oscillator Collapse Physical Unclonable Function Based on FinFET
IEEE Access, 2021 The main purpose of this paper is to achieve ultra-low power Physical Unclonable Function (PUF) to meet the requirements for Internet of Things (IoT) applications.
Amin A. Zayed +3 more
doaj +1 more source
IEEE Access, 2022 Design-space exploration for low-power manycore design is a daunting and time-consuming task which requires some complex tools and frameworks to achieve. In the presence of process variation, the problem becomes even more challenging, especially the time
Sohaib Majzoub +4 more
doaj +1 more source
IEEE Access, 2022 NAND flash memory is becoming smaller and denser to have a larger storage capacity as technologies related to fine processes are developed. As a side effect of high-density integration, the memory can be vulnerable to circuit-level noise such as random ...
Minyoung Hwang +5 more
doaj +1 more source
Representing Process Variation with a Process Family [PDF]
, 2007 The formalization of process definitions has been an invaluable aid in many domains. However, noticeable variations in processes start to emerge as precise details are added to process definitions. While each such variation gives rise to a different process, these processes might more usefully be considered as variants of each other, rather than ...
Borislava I. Simidchieva +2 more
openaire +1 more source
Variational Implicit Processes
CoRR, 2018 We introduce the implicit processes (IPs), a stochastic process that places implicitly defined multivariate distributions over any finite collections of random variables. IPs are therefore highly flexible implicit priors over functions, with examples including data simulators, Bayesian neural networks and non-linear transformations of stochastic ...
Ma, Chao +2 more
openaire +3 more sources
An Innovative Indicator to Evaluate DRAM Cell Transistor Leakage Current Distribution
IEEE Journal of the Electron Devices Society, 2018 This paper is the first to propose an innovative method for measuring variations in dynamic random access memory (DRAM) cell transistors. Structural dispersion induces an extremely high cell leakage current, which determines aspects of DRAM performance ...
Min Hee Cho +7 more
doaj +1 more source
AVATAR: NN-Assisted Variation Aware Timing Analysis and Reporting for Hardware Trojan Detection
IEEE Access, 2021 This paper presents AVATAR, a learning-assisted Trojan testing flow to detect hardware Trojans placed into fabricated ICs at an untrusted foundry, without needing a Golden IC.
Ashkan Vakil +4 more
doaj +1 more source