Results 1 to 10 of about 389,022 (171)
PyRates-A Python framework for rate-based neural simulations. [PDF]
PLoS ONE, 2019 In neuroscience, computational modeling has become an important source of insight into brain states and dynamics. A basic requirement for computational modeling studies is the availability of efficient software for setting up models and performing ...
Richard Gast +5 more
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Neural simulations on multi-core architectures [PDF]
Frontiers in Neuroinformatics, 2009 Neuroscience is witnessing increasing knowledge about the anatomy and electrophysiological properties of neurons and their connectivity, leading to an ever increasing computational complexity of neural simulations.
Hubert Eichner +2 more
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Neural Camera Simulators [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 We present a controllable camera simulator based on deep neural networks to synthesize raw image data under different camera settings, including exposure time, ISO, and aperture. The proposed simulator includes an exposure module that utilizes the principle of modern lens designs for correcting the luminance level. It also contains a noise module using
Ouyang, Hao +4 more
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Mapping and Validating a Point Neuron Model on Intel's Neuromorphic Hardware Loihi
Frontiers in Neuroinformatics, 2022 Neuromorphic hardware is based on emulating the natural biological structure of the brain. Since its computational model is similar to standard neural models, it could serve as a computational accelerator for research projects in the field of ...
Srijanie Dey, Alexander Dimitrov
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Simulating Neural Network Processors [PDF]
Wireless Communications and Mobile Computing, 2022 Deep learning has achieved competing results compared with human beings in many fields. Traditionally, deep learning networks are executed on CPUs and GPUs. In recent years, more and more neural network accelerators have been introduced in both academia and industry to improve the performance and energy efficiency for deep learning networks.
Jian Hu, Xianlong Zhang, Xiaohua Shi
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Sensitivity analysis of point neuron model simulations implemented on neuromorphic hardware
Frontiers in Neuroscience, 2023 With the ongoing growth in the field of neuro-inspired computing, newly arriving computational architectures demand extensive validation and testing against existing benchmarks to establish their competence and value.
Srijanie Dey, Alexander G. Dimitrov
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ACM Transactions on Graphics, 2022 We present a general framework for the garment animation problem through unsupervised deep learning inspired in physically based simulation. Existing trends in the literature already explore this possibility. Nonetheless, these approaches do not handle cloth dynamics.
Bertiche, Hugo +2 more
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Inference Using Simulated Neural Moments [PDF]
Econometrics, 2021 This paper studies method of simulated moments (MSM) estimators that are implemented using Bayesian methods, specifically Markov chain Monte Carlo (MCMC). Motivation and theory for the methods is provided by Chernozhukov and Hong (2003). The paper shows, experimentally, that confidence intervals using these methods may have coverage which is far from ...
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, 2022 Simulated annealing (SA) is a stochastic global optimisation technique applicable to a wide range of discrete and continuous variable problems. Despite its simplicity, the development of an effective SA optimiser for a given problem hinges on a handful of carefully handpicked components; namely, neighbour proposal distribution and temperature annealing
Correia, Alvaro H. C. +2 more
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Nanomaterials, 2021 The substitution of time- and labor-intensive empirical research as well as slow finite difference time domain (FDTD) simulations with revolutionary techniques such as artificial neural network (ANN)-based predictive modeling is the next trend in the ...
Ehsan Vahidzadeh, Karthik Shankar
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