Michael Pfeiffer

Publication Activity (10 Years)

Years Active: 2007-2023
Publications (10 Years): 36

Top Topics

Mutual Information Maximization

Primary Visual Cortex

Deep Belief Networks

Top Venues

PLoS Comput. Biol.

Publications

Alexander Kugele, Thomas Pfeil, Michael Pfeiffer, Elisabetta Chicca
How Many Events Make an Object? Improving Single-frame Object Detection on the 1 Mpx Dataset. CVPR Workshops (2023)
Kanil Patel, William Beluch, Kilian Rambach, Adriana-Eliza Cozma, Michael Pfeiffer, Bin Yang
Investigation of Uncertainty of Deep Learning-based Object Classification on Radar Spectra. CoRR (2021)
Alexander Kugele, Thomas Pfeil, Michael Pfeiffer, Elisabetta Chicca
Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision. GCPR (2021)
Alexander Kugele, Thomas Pfeil, Michael Pfeiffer, Elisabetta Chicca
Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision. CoRR (2021)
Kanil Patel, William Beluch, Kilian Rambach, Michael Pfeiffer, Bin Yang
Improving Uncertainty of Deep Learning-based Object Classification on Radar Spectra using Label Smoothing. CoRR (2021)
Robert Haas, Michael Pfeiffer
Brain-inspired Computing - Introduction to the Special Theme. ERCIM News 2021 (125) (2021)
Kanil Patel, William H. Beluch, Bin Yang, Michael Pfeiffer, Dan Zhang
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning. ICLR (2021)
Kanil Patel, William Beluch, Bin Yang, Michael Pfeiffer, Dan Zhang
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning. CoRR (2020)
Kanil Patel, William Beluch, Dan Zhang, Michael Pfeiffer, Bin Yang
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration. ICPR (2020)
Armin Runge, Thomas Wenzel, Dimitrios Bariamis, Benedikt Sebastian Staffler, Lucas Rêgo Drumond, Michael Pfeiffer
Bosch Deep Learning Hardware Benchmark. CoRR (2020)
Pegah Kassraian-Fard, Michael Pfeiffer, Roman Bauer
A generative growth model for thalamocortical axonal branching in primary visual cortex. PLoS Comput. Biol. 16 (2) (2020)
Laura Beggel, Michael Pfeiffer, Bernd Bischl
Robust Anomaly Detection in Images using Adversarial Autoencoders. CoRR (2019)
Kanil Patel, William Beluch, Dan Zhang, Michael Pfeiffer, Bin Yang
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration. CoRR (2019)
Laura Beggel, Bernhard X. Kausler, Martin Schiegg, Michael Pfeiffer, Bernd Bischl
Time series anomaly detection based on shapelet learning. Comput. Stat. 34 (3) (2019)
Laura Beggel, Michael Pfeiffer, Bernd Bischl
Robust Anomaly Detection in Images Using Adversarial Autoencoders. ECML/PKDD (1) (2019)
Nikola I. Nikolov, Michael Pfeiffer, Richard H. R. Hahnloser
Data-driven Summarization of Scientific Articles. CoRR (2018)
Cornelia Fermüller, Fang Wang, Yezhou Yang, Konstantinos Zampogiannis, Yi Zhang, Francisco Barranco, Michael Pfeiffer
Prediction of Manipulation Actions. Int. J. Comput. Vis. 126 (2-4) (2018)
Korsuk Sirinukunwattana, Josien P. W. Pluim, Hao Chen, Xiaojuan Qi, Pheng-Ann Heng, Yun Bo Guo, Li Yang Wang, Bogdan J. Matuszewski, Elia Bruni, Urko Sanchez, Anton Böhm, Olaf Ronneberger, Bassem Ben Cheikh, Daniel Racoceanu, Philipp Kainz, Michael Pfeiffer, Martin Urschler, David R. J. Snead, Nasir M. Rajpoot
Gland segmentation in colon histology images: The glas challenge contest. Medical Image Anal. 35 (2017)
Dora Sumislawska, Qiao Ning, Michael Pfeiffer, Giacomo Indiveri
Wide dynamic range weights and biologically realistic synaptic dynamics for spike-based learning circuits. ISCAS (2016)
Jonathan Binas, Giacomo Indiveri, Michael Pfeiffer
Spiking analog VLSI neuron assemblies as constraint satisfaction problem solvers. ISCAS (2016)
Jonathan Binas, Giacomo Indiveri, Michael Pfeiffer
Deep counter networks for asynchronous event-based processing. CoRR (2016)
Korsuk Sirinukunwattana, Josien P. W. Pluim, Hao Chen, Xiaojuan Qi, Pheng-Ann Heng, Yun Bo Guo, Li Yang Wang, Bogdan J. Matuszewski, Elia Bruni, Urko Sanchez, Anton Böhm, Olaf Ronneberger, Bassem Ben Cheikh, Daniel Racoceanu, Philipp Kainz, Michael Pfeiffer, Martin Urschler, David R. J. Snead, Nasir M. Rajpoot
Gland Segmentation in Colon Histology Images: The GlaS Challenge Contest. CoRR (2016)
Bodo Rueckauer, Iulia-Alexandra Lungu, Yuhuang Hu, Michael Pfeiffer
Theory and Tools for the Conversion of Analog to Spiking Convolutional Neural Networks. CoRR (2016)
Junhaeng Lee, Tobi Delbrück, Michael Pfeiffer
Training Deep Spiking Neural Networks using Backpropagation. CoRR (2016)
Daniel Neil, Michael Pfeiffer, Shih-Chii Liu
Learning to be efficient: algorithms for training low-latency, low-compute deep spiking neural networks. SAC (2016)
Daniel Neil, Michael Pfeiffer, Shih-Chii Liu
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences. CoRR (2016)
Jonathan Binas, Daniel Neil, Giacomo Indiveri, Shih-Chii Liu, Michael Pfeiffer
Precise deep neural network computation on imprecise low-power analog hardware. CoRR (2016)
Daniel Neil, Michael Pfeiffer, Shih-Chii Liu
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences. NIPS (2016)
Cornelia Fermüller, Fang Wang, Yezhou Yang, Konstantinos Zampogiannis, Yi Zhang, Francisco Barranco, Michael Pfeiffer
Prediction of Manipulation Actions. CoRR (2016)
Evangelos Stromatias, Daniel Neil, Francesco Galluppi, Michael Pfeiffer, Shih-Chii Liu, Steve B. Furber
Scalable energy-efficient, low-latency implementations of trained spiking Deep Belief Networks on SpiNNaker. IJCNN (2015)
Peter U. Diehl, Daniel Neil, Jonathan Binas, Matthew Cook, Shih-Chii Liu, Michael Pfeiffer
Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing. IJCNN (2015)
Jonathan Binas, Giacomo Indiveri, Michael Pfeiffer
Local structure helps learning optimized automata in recurrent neural networks. IJCNN (2015)
Jonathan Binas, Giacomo Indiveri, Michael Pfeiffer
Spiking Analog VLSI Neuron Assemblies as Constraint Satisfaction Problem Solvers. CoRR (2015)
Tobi Delbrück, Michael Pfeiffer, R. Juston, Garrick Orchard, Elias Mueggler, Alejandro Linares-Barranco, M. W. Tilden
Human vs. computer slot car racing using an event and frame-based DAVIS vision sensor. ISCAS (2015)
Evangelos Stromatias, Daniel Neil, Francesco Galluppi, Michael Pfeiffer, Shih-Chii Liu, Steve B. Furber
Live demonstration: Handwritten digit recognition using spiking deep belief networks on SpiNNaker. ISCAS (2015)
Philipp Kainz, Michael Pfeiffer, Martin Urschler
Semantic Segmentation of Colon Glands with Deep Convolutional Neural Networks and Total Variation Segmentation. CoRR (2015)
Jonathan Binas, Ueli Rutishauser, Giacomo Indiveri, Michael Pfeiffer
Learning and stabilization of winner-take-all dynamics through interacting excitatory and inhibitory plasticity. Frontiers Comput. Neurosci. 8 (2014)
Roman Bauer, Frédéric Zubler, Sabina S. Pfister, Andreas Hauri, Michael Pfeiffer, Dylan R. Muir, Rodney J. Douglas
Developmental Self-Construction and -Configuration of Functional Neocortical Neuronal Networks. PLoS Comput. Biol. 10 (12) (2014)
Junhaeng Lee, Tobi Delbrück, Michael Pfeiffer, Paul K. J. Park, Chang-Woo Shin, Hyunsurk Ryu, Byung-Chang Kang
Real-Time Gesture Interface Based on Event-Driven Processing From Stereo Silicon Retinas. IEEE Trans. Neural Networks Learn. Syst. 25 (12) (2014)
Bernhard Nessler, Michael Pfeiffer, Lars Buesing, Wolfgang Maass
Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity. PLoS Comput. Biol. 9 (4) (2013)
Sadique Sheik, Michael Pfeiffer, Fabio Stefanini, Giacomo Indiveri
Spatio-temporal Spike Pattern Classification in Neuromorphic Systems. Living Machines (2013)
Junhaeng Lee, Tobi Delbrück, Paul K. J. Park, Michael Pfeiffer, Chang-Woo Shin, Hyunsurk Ryu, Byung-Chang Kang
Live demonstration: Gesture-based remote control using stereo pair of dynamic vision sensors. ISCAS (2012)
Michael Pfeiffer, Bernhard Nessler, Rodney J. Douglas, Wolfgang Maass
Reward-Modulated Hebbian Learning of Decision Making. Neural Comput. 22 (6) (2010)
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
STDP enables spiking neurons to detect hidden causes of their inputs. NIPS (2009)
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
Hebbian Learning of Bayes Optimal Decisions. NIPS (2008)
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs. ECML (2007)