Malte J Rasch

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Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindVerified email at gatsby.ucl.ac.uk
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Alex SmolaBoson AIVerified email at smola.org
Karsten BorgwardtDirector, Max Planck Institute of BiochemistryVerified email at biochem.mpg.de
Tayfun GokmenPrinceton University, IBM T. J. Watson Research CenterVerified email at us.ibm.com
Nikos LogothetisVisiting Professor of Neuroscience, Stanford UniversityVerified email at stanford.edu
Si WuPeking UniversityVerified email at pku.edu.cn
Abu SebastianDistinguished Scientist, IBM Research - ZurichVerified email at zurich.ibm.com
Manuel Le GalloIBM Research-ZurichVerified email at zurich.ibm.com
Hsinyu TsaiResearch Staff Member, IBMVerified email at us.ibm.com
Xiaohui zhangState Key Laboratory of Cognitive Neuroscience & Learning, Beijine Normal UniversityVerified email at bnu.edu.cn
Charles MackinIBM Research, MITVerified email at ibm.com
Geoffrey W. BurrIBM Research - AlmadenVerified email at us.ibm.com
Wolfgang MaassProfessor of Computer Science, Graz University of TechnologyVerified email at igi.tugraz.at
Christoph D. DahlTaipei Medical University, Brain and Consciousness Research CenterVerified email at tmu.edu.tw
Hans-Peter KriegelProfessor für Informatik, Ludwig-Maximilians-University MunichVerified email at dbs.ifi.lmu.de
Marcelo A. MontemurroSchool of Mathematics and Statistics at The Open UniversityVerified email at open.ac.uk
Stefano PanzeriUniversity Medical Center Hamburg-Eppendorf (UKE), and Istituto Italiano di TecnologiaVerified email at uke.de
Ikuma AdachiKyoto University Primate Research InstituteVerified email at kyoto-u.ac.jp
Chien-Chung ChenNational Taiwan UniversityVerified email at ntu.edu.tw

Malte J Rasch

Sony AI (previously: IBM Research AI)

Verified email at sony.com

Computational Neuroscience Machine learning Analog in-memory computing AI for chip design


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A kernel two-sample test A Gretton, KM Borgwardt, MJ Rasch, B Schölkopf, A Smola The Journal of Machine Learning Research 13 (1), 723-773, 2012	5833	2012
A kernel method for the two-sample-problem A Gretton, KM Borgwardt, M Rasch, B Schölkopf, AJ Smola Advances in neural information processing systems, 513-520, 2006	2679	2006
Integrating structured biological data by kernel maximum mean discrepancy KM Borgwardt, A Gretton, MJ Rasch, HP Kriegel, B Schölkopf, AJ Smola Bioinformatics 22 (14), e49-e57, 2006	1740	2006
Phase-of-firing coding of natural visual stimuli in primary visual cortex MA Montemurro, MJ Rasch, Y Murayama, NK Logothetis, S Panzeri Current biology 18 (5), 375-380, 2008	429	2008
A functional hypothesis for adult hippocampal neurogenesis: avoidance of catastrophic interference in the dentate gyrus L Wiskott, MJ Rasch, G Kempermann Hippocampus 16 (3), 329-343, 2006	377	2006
Distinct inhibitory circuits orchestrate cortical beta and gamma band oscillations G Chen, Y Zhang, X Li, X Zhao, Q Ye, Y Lin, HW Tao, MJ Rasch, X Zhang Neuron 96 (6), 1403-1418. e6, 2017	299	2017
Inferring spike trains from local field potentials MJ Rasch, A Gretton, Y Murayama, W Maass, NK Logothetis Journal of neurophysiology 99 (3), 1461-1476, 2008	271	2008
A distinct entorhinal cortex to hippocampal CA1 direct circuit for olfactory associative learning Y Li, J Xu, Y Liu, J Zhu, N Liu, W Zeng, N Huang, MJ Rasch, H Jiang, X Gu, ... Nature neuroscience 20 (4), 559-570, 2017	190	2017
Perceptual training continuously refines neuronal population codes in primary visual cortex Y Yan+, MJ Rasch+, M Chen+, X Xiang, M Huang, S Wu, W Li* Nature neuroscience 17 (10), 1380-1387, 2014	146	2014
A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inference M Le Gallo, R Khaddam-Aljameh, M Stanisavljevic, A Vasilopoulos, ... Nature Electronics 6 (9), 680-693, 2023	99	2023
A flexible and fast PyTorch toolkit for simulating training and inference on analog crossbar arrays MJ Rasch, D Moreda, T Gokmen, M Le Gallo, F Carta, C Goldberg, ... 2021 IEEE 3rd international conference on artificial intelligence circuits …, 2021	98	2021
From neurons to circuits: linear estimation of local field potentials M Rasch, NK Logothetis, G Kreiman Journal of Neuroscience 29 (44), 13785-13796, 2009	91	2009
A kernel approach to comparing distributions A Gretton, KM Borgwardt, M Rasch, B Schölkopf, AJ Smola Proceedings of the national conference on artificial intelligence 22 (2), 1637, 2007	78	2007
Autapses enhance bursting and coincidence detection in neocortical pyramidal cells L Yin, R Zheng, W Ke, Q He, Y Zhang, J Li, B Wang, Z Mi, Y Long, ... Nature communications 9 (1), 4890, 2018	73	2018
Decentralized multisensory information integration in neural systems WH Zhang, A Chen, MJ Rasch, S Wu Journal of Neuroscience 36 (2), 532-547, 2016	63	2016
Training LSTM networks with resistive cross-point devices T Gokmen, MJ Rasch, W Haensch Frontiers in neuroscience 12, 745, 2018	61	2018
Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators MJ Rasch, C Mackin, M Le Gallo, A Chen, A Fasoli, F Odermatt, N Li, ... Nature communications 14 (1), 5282, 2023	53	2023
Experience-dependent emergence of beta and gamma band oscillations in the primary visual cortex during the critical period G Chen, MJ Rasch, R Wang, X Zhang Scientific reports 5 (1), 17847, 2015	49	2015
Selective modulation of axonal sodium channel subtypes by 5-HT1A receptor in cortical pyramidal neuron L Yin, MJ Rasch, Q He, S Wu, F Dou, Y Shu Cerebral Cortex 27 (1), 509-521, 2017	44	2017
On-chip trainable 1.4 M 6T2R PCM synaptic array with 1.6 K stochastic LIF neurons for spiking RBM M Ishii, S Kim, S Lewis, A Okazaki, J Okazawa, M Ito, M Rasch, W Kim, ... 2019 IEEE International Electron Devices Meeting (IEDM), 14.2. 1-14.2. 4, 2019	38	2019

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