Michael Pfeiffer

46 papers A* 1B 4C 5Misc 1Journal 27Unranked 8

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