Michael Pfeiffer

Affiliations:
  • Bosch Center for Artificial Intelligence, Renningen, Germany
  • ETH Zurich, Switzerland (former)
  • University of Zurich, Institute of Neuroinformatics, Switzerland (former)
  • Graz University of Technology, Austria (former)


According to our database1, Michael Pfeiffer authored at least 37 papers between 2007 and 2021.

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Timeline

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Bibliography

2021
Brain-inspired Computing - Introduction to the Special Theme.
ERCIM News, 2021

Improving Uncertainty of Deep Learning-based Object Classification on Radar Spectra using Label Smoothing.
CoRR, 2021

Investigation of Uncertainty of Deep Learning-based Object Classification on Radar Spectra.
CoRR, 2021

Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
A generative growth model for thalamocortical axonal branching in primary visual cortex.
PLoS Comput. Biol., 2020

Bosch Deep Learning Hardware Benchmark.
CoRR, 2020

On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019
Time series anomaly detection based on shapelet learning.
Comput. Stat., 2019

On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration.
CoRR, 2019

Robust Anomaly Detection in Images Using Adversarial Autoencoders.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

2018
Prediction of Manipulation Actions.
Int. J. Comput. Vis., 2018

Data-driven Summarization of Scientific Articles.
CoRR, 2018

2017
Gland segmentation in colon histology images: The glas challenge contest.
Medical Image Anal., 2017

2016
Theory and Tools for the Conversion of Analog to Spiking Convolutional Neural Networks.
CoRR, 2016

Training Deep Spiking Neural Networks using Backpropagation.
CoRR, 2016

Precise deep neural network computation on imprecise low-power analog hardware.
CoRR, 2016

Deep counter networks for asynchronous event-based processing.
CoRR, 2016

Learning to be efficient: algorithms for training low-latency, low-compute deep spiking neural networks.
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Wide dynamic range weights and biologically realistic synaptic dynamics for spike-based learning circuits.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

Spiking analog VLSI neuron assemblies as constraint satisfaction problem solvers.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

2015
Semantic Segmentation of Colon Glands with Deep Convolutional Neural Networks and Total Variation Segmentation.
CoRR, 2015

Live demonstration: Handwritten digit recognition using spiking deep belief networks on SpiNNaker.
Proceedings of the 2015 IEEE International Symposium on Circuits and Systems, 2015

Human vs. computer slot car racing using an event and frame-based DAVIS vision sensor.
Proceedings of the 2015 IEEE International Symposium on Circuits and Systems, 2015

Scalable energy-efficient, low-latency implementations of trained spiking Deep Belief Networks on SpiNNaker.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Local structure helps learning optimized automata in recurrent neural networks.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014
Real-Time Gesture Interface Based on Event-Driven Processing From Stereo Silicon Retinas.
IEEE Trans. Neural Networks Learn. Syst., 2014

Developmental Self-Construction and -Configuration of Functional Neocortical Neuronal Networks.
PLoS Comput. Biol., 2014

Learning and stabilization of winner-take-all dynamics through interacting excitatory and inhibitory plasticity.
Frontiers Comput. Neurosci., 2014

2013
Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity.
PLoS Comput. Biol., 2013

Spatio-temporal Spike Pattern Classification in Neuromorphic Systems.
Proceedings of the Biomimetic and Biohybrid Systems, 2013

2012
Live demonstration: Gesture-based remote control using stereo pair of dynamic vision sensors.
Proceedings of the 2012 IEEE International Symposium on Circuits and Systems, 2012

2010
Reward-Modulated Hebbian Learning of Decision Making.
Neural Comput., 2010

2009
STDP enables spiking neurons to detect hidden causes of their inputs.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008
Hebbian Learning of Bayes Optimal Decisions.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs.
Proceedings of the Machine Learning: ECML 2007, 2007


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