List of works - Mihai A Petrovici

25th Annual Computational Neuroscience Meeting: CNS-2016

scientific article

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3.

scientific article

A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems

scientific article

Accelerated Physical Emulation of Bayesian Inference in Spiking Neural Networks

scientific article published on 14 November 2019

Characterization and compensation of network-level anomalies in mixed-signal neuromorphic modeling platforms ⬇️

scientific article

Cortical oscillations support sampling-based computations in spiking neural networks

scientific article published on 24 March 2022

Demonstrating Advantages of Neuromorphic Computation: A Pilot Study

scientific article published on 26 March 2019

Deterministic networks for probabilistic computing

scientific article published on 04 December 2019

Deterministic neural networks as sources of uncorrelated noise for probabilistic computations

scientific article published on 4 December 2015

Long-range angular correlations on the near and away side in p–Pb collisions at s NN = 5.02 TeV

article

Measurement of prompt J/ψ and beauty hadron production cross sections at mid-rapidity in pp collisions at √s=7 TeV

article by Betty Abelev et al published November 2012 in Journal of High Energy Physics

Natural-gradient learning for spiking neurons

scientific article published in 2022

Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons ⬇️

scientific article published on 12 February 2015

Six networks on a universal neuromorphic computing substrate

scientific article published on 18 February 2013

Spiking neurons with short-term synaptic plasticity form superior generative networks

scientific article published on 13 July 2018

Stochastic inference with spiking neurons in the high-conductance state ⬇️

scientific article published on 20 October 2016

Stochasticity from function - Why the Bayesian brain may need no noise

scientific article published on 19 August 2019

The high-conductance state enables neural sampling in networks of LIF neurons ⬇️

scientific article published on 4 December 2015

Underlying Event measurements in pp collisions at √𝑠=0.9 and 7 TeV with the ALICE experiment at the LHC

scholarly article

List of works by Mihai A Petrovici

25th Annual Computational Neuroscience Meeting: CNS-2016

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3.

A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems

Accelerated Physical Emulation of Bayesian Inference in Spiking Neural Networks

Characterization and compensation of network-level anomalies in mixed-signal neuromorphic modeling platforms ⬇️

Cortical oscillations support sampling-based computations in spiking neural networks

Demonstrating Advantages of Neuromorphic Computation: A Pilot Study

Deterministic networks for probabilistic computing

Deterministic neural networks as sources of uncorrelated noise for probabilistic computations

Long-range angular correlations on the near and away side in p–Pb collisions at s NN = 5.02 TeV

Measurement of prompt J/ψ and beauty hadron production cross sections at mid-rapidity in pp collisions at √s=7 TeV

Natural-gradient learning for spiking neurons

Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons ⬇️

Six networks on a universal neuromorphic computing substrate

Spiking neurons with short-term synaptic plasticity form superior generative networks

Stochastic inference with spiking neurons in the high-conductance state ⬇️

Stochasticity from function - Why the Bayesian brain may need no noise

The high-conductance state enables neural sampling in networks of LIF neurons ⬇️

Underlying Event measurements in pp collisions at √𝑠=0.9 and 7 TeV with the ALICE experiment at the LHC