Mihai A. Petrovici

发表

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

Johannes Schemmel, Karlheinz Meier, Dejan Pecevski, 2014, Front. Comput. Neurosci..

Demonstrating Advantages of Neuromorphic Computation: A Pilot Study

Johannes Schemmel, Karlheinz Meier, Syed Ahmed Aamir, 2018, Front. Neurosci..

Stochastic inference with spiking neurons in the high-conductance state

Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici, 2016, Physical review. E.

Fast and deep neuromorphic learning with time-to-first-spike coding pdf

Walter Senn, Laura Kriener, Mihai A. Petrovici, 2019, ArXiv.

Neuromorphic hardware in the loop: Training a deep spiking network on the BrainScaleS wafer-scale system

Robert A. Legenstein, Wolfgang Maass, Andreas Hartel, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Conductance-based dendrites perform reliability-weighted opinion pooling

Walter Senn, Jakob Jordan, Mihai A. Petrovici, 2020, NICE.

Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms

Johannes Schemmel, Karlheinz Meier, Anders Lansner, 2014, PloS one.

Deterministic networks for probabilistic computing

Johannes Schemmel, Karlheinz Meier, Markus Diesmann, 2017, Scientific Reports.

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

Silvestro Micera, Johannes Schemmel, Szabolcs Káli, 2017, BMC Neuroscience.

Natural gradient learning for spiking neurons

Walter Senn, Mihai A. Petrovici, Elena Kreutzer, 2020, NICE.

Structural plasticity on an accelerated analog neuromorphic hardware system

Mihai A. Petrovici, Korbinian Schreiber, Sebastian Billaudelle, 2019, Neural Networks.

Pattern representation and recognition with accelerated analog neuromorphic systems

Robert A. Legenstein, Wolfgang Maass, René Schüffny, 2017, 2017 IEEE International Symposium on Circuits and Systems (ISCAS).

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

Johannes Schemmel, Karlheinz Meier, Anders Lansner, 2010, Biological Cybernetics.

Bridging the gap between software simulation and emulation on neuromorphic hardware: An investigation of causes, effects and compensation of network-level anomalies in a mixed-signal waferscale neuromorphic modeling platform pdf

Johannes Schemmel, Karlheinz Meier, Anders Lansner, 2014, ArXiv.

Form vs. function: theory and models for neuronal substrates

Mihai A. Petrovici, Mihai A. Petrovici, 2015 .

Spiking neuromorphic chip learns entangled quantum states pdf

Mihai A. Petrovici, Thomas Gasenzer, Sebastian Billaudelle, 2020, ArXiv.

Robustness from structure: Inference with hierarchical spiking networks on analog neuromorphic hardware

Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

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

Johannes Schemmel, Karlheinz Meier, Walter Senn, 2018, Neural Networks.

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

Johannes Schemmel, Karlheinz Meier, Walter Senn, 2018, Scientific Reports.

Accelerated Physical Emulation of Bayesian Inference in Spiking Neural Networks

Paul Müller, Andreas Hartel, Eric Müller, 2018, Front. Neurosci..

Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate

Andreas Hartel, Walter Senn, Gerd Kiene, 2020, ISCAS.

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

Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici, 2015, BMC Neuroscience.

Stochastic inference with deterministic spiking neurons pdf

Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici, 2013, ArXiv.

Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network pdf

Eric Müller, Mihai A. Petrovici, Timo Wunderlich, 2019, ICANN.

Evolving to learn: discovering interpretable plasticity rules for spiking networks

Walter Senn, Jakob Jordan, Mihai A. Petrovici, 2020 .

Six Networks on a Universal Neuromorphic Computing Substrate

Johannes Schemmel, Karlheinz Meier, Michael Schmuker, 2012, Front. Neurosci..