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Anders Lansner
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2020 – today
- 2024
- [j54]Jiawei Xu
, Yi Zheng, Feng Li
Modeling Cycle-to-Cycle Variation in Memristors for In-Situ Unsupervised Trace-STDP Learning. IEEE Trans. Circuits Syst. II Express Briefs 71(2): 627-631 (2024) - [c30]Deyu Wang
FPGA-Based HPC for Associative Memory System. ASPDAC 2024: 52-57 - [i13]Anders Lansner, Naresh Balaji Ravichandran, Pawel Andrzej Herman:
Benchmarking Hebbian learning rules for associative memory. CoRR abs/2401.00335 (2024) - [i12]Naresh Balaji Ravichandran, Anders Lansner, Pawel Andrzej Herman:
Spiking representation learning for associative memories. CoRR abs/2406.03054 (2024) - [i11]Naresh Balaji Ravichandran, Anders Lansner, Pawel Andrzej Herman:
Unsupervised representation learning with Hebbian synaptic and structural plasticity in brain-like feedforward neural networks. CoRR abs/2406.04733 (2024) - 2023
- [j53]Deyu Wang
A Memristor-Based Learning Engine for Synaptic Trace-Based Online Learning. IEEE Trans. Biomed. Circuits Syst. 17(5): 1153-1165 (2023) - [c29]Naresh Balaji Ravichandran, Anders Lansner, Pawel Andrzej Herman:
Spiking neural networks with Hebbian plasticity for unsupervised representation learning. ESANN 2023 - [i10]Anders Lansner, Florian Fiebig, Pawel Andrzej Herman:
Hebbian fast plasticity and working memory. CoRR abs/2304.06626 (2023) - [i9]Naresh Balaji Ravichandran, Anders Lansner, Pawel Andrzej Herman:
Spiking neural networks with Hebbian plasticity for unsupervised representation learning. CoRR abs/2305.03866 (2023) - 2022
- [c28]Deyu Wang
Memristor-Based In-Circuit Computation for Trace-Based STDP. AICAS 2022: 1-4 - [c27]Patrícia Pereira
Incremental Attractor Neural Network Modelling of the Lifespan Retrieval Curve. IJCNN 2022: 1-7 - [c26]Anders Lansner:
CORtEX 2022 Invited Speaker 2: Brain-like machine learning using BCPNN. IPDPS Workshops 2022: 1238 - [c25]Naresh Balaji Ravichandran
Brain-like Combination of Feedforward and Recurrent Network Components Achieves Prototype Extraction and Robust Pattern Recognition. LOD (2) 2022: 488-501 - [i8]Naresh Balaji Ravichandran, Anders Lansner, Pawel Andrzej Herman:
Brain-like combination of feedforward and recurrent network components achieves prototype extraction and robust pattern recognition. CoRR abs/2206.15036 (2022) - 2021
- [c24]Jiawei Xu, Deyu Wang
A Memristor Model with Concise Window Function for Spiking Brain-Inspired Computation. AICAS 2021: 1-4 - [c23]Dimitrios Stathis
Approximate computation of post-synaptic spikes reduces bandwidth to synaptic storage in a model of cortex. DATE 2021: 685-688 - [c22]Naresh Balaji Ravichandran
Semi-supervised learning with Bayesian Confidence Propagation Neural Network. ESANN 2021 - [c21]Artur Podobas, Martin Svedin, Steven Wei Der Chien
StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs. HEART 2021: 8:1-8:6 - [c20]Naresh Balaji Ravichandran
Brain-Like Approaches to Unsupervised Learning of Hidden Representations - A Comparative Study. ICANN (5) 2021: 162-173 - [i7]Artur Podobas, Martin Svedin, Steven Wei Der Chien, Ivy Bo Peng, Naresh Balaji Ravichandran, Pawel Andrzej Herman, Anders Lansner, Stefano Markidis:
StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs. CoRR abs/2106.05373 (2021) - [i6]Naresh Balaji Ravichandran, Anders Lansner, Pawel Andrzej Herman:
Semi-supervised learning with Bayesian Confidence Propagation Neural Network. CoRR abs/2106.15546 (2021) - 2020
- [j52]Dimitrios Stathis
eBrainII: a 3 kW Realtime Custom 3D DRAM Integrated ASIC Implementation of a Biologically Plausible Model of a Human Scale Cortex. J. Signal Process. Syst. 92(11): 1323-1343 (2020) - [c19]Gianluca Villani, Matin Jafarian, Anders Lansner, Karl Henrik Johansson:
Analysis of free recall dynamics of an abstract working memory model. ACC 2020: 2562-2567 - [c18]Naresh Balaji Ravichandran
Learning representations in Bayesian Confidence Propagation neural networks. IJCNN 2020: 1-7 - [c17]Lizheng Liu, Deyu Wang
A FPGA-based Hardware Accelerator for Bayesian Confidence Propagation Neural Network. NorCAS 2020: 1-6 - [i5]Naresh Balaji Ravichandran, Anders Lansner, Pawel Andrzej Herman:
Learning representations in Bayesian Confidence Propagation neural networks. CoRR abs/2003.12415 (2020) - [i4]Naresh Balaji Ravichandran, Anders Lansner, Pawel Andrzej Herman:
Brain-like approaches to unsupervised learning of hidden representations - a comparative study. CoRR abs/2005.03476 (2020)
2010 – 2019
- 2019
- [j51]Nikolaos Chrysanthidis
Introducing double bouquet cells into a modular cortical associative memory model. J. Comput. Neurosci. 47(2-3): 223-230 (2019) - [c16]Ramon H. Martinez
Sequence Disambiguation with Synaptic Traces in Associative Neural Networks. ICANN (1) 2019: 793-805 - [i3]Gianluca Villani, Matin Jafarian
Analysis of free recall dynamics of an abstract working memory model. CoRR abs/1910.11742 (2019) - [i2]Dimitrios Stathis, Chirag Sudarshan, Yu Yang, Matthias Jung, Syed Mohammad Asad Hassan Jafri, Christian Weis, Ahmed Hemani, Anders Lansner, Norbert Wehn:
eBrainII: A 3 kW Realtime Custom 3D DRAM integrated ASIC implementation of a Biologically Plausible Model of a Human Scale Cortex. CoRR abs/1911.00889 (2019) - 2018
- [c15]Naresh Balaji Ravichandran, Fangkai Yang, Christopher Peters, Anders Lansner, Pawel Andrzej Herman:
Pedestrian simulation as multi-objective reinforcement learning. IVA 2018: 307-312 - 2017
- [c14]Pawel Andrzej Herman, Simon Benjaminsson, Anders Lansner:
Odor recognition in an attractor network model of the mammalian olfactory cortex. IJCNN 2017: 3561-3568 - 2016
- [j50]Philip J. Tully
Spike-Based Bayesian-Hebbian Learning of Temporal Sequences. PLoS Comput. Biol. 12(5) (2016) - 2015
- [j49]Alberto Mazzoni
Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models. PLoS Comput. Biol. 11(12) (2015) - 2014
- [j48]Florian Fiebig
Memory consolidation from seconds to weeks: a three-stage neural network model with autonomous reinstatement dynamics. Frontiers Comput. Neurosci. 8: 64 (2014) - [c13]Anders Lansner, Ahmed Hemani, Nasim Farahini:
Spiking brain models: Computation, memory and communication constraints for custom hardware implementation. ASP-DAC 2014: 556-562 - [c12]Nasim Farahini, Ahmed Hemani, Anders Lansner, Fabien Clermidy, Christer Svensson:
A scalable custom simulation machine for the Bayesian Confidence Propagation Neural Network model of the brain. ASP-DAC 2014: 578-585 - [c11]Bernhard A. Kaplan, Mina A. Khoei, Anders Lansner, Laurent U. Perrinet
Signature of an anticipatory response in area VI as modeled by a probabilistic model and a spiking neural network. IJCNN 2014: 3205-3212 - [i1]Mihai A. Petrovici, Bernhard Vogginger, Paul Müller, Oliver Breitwieser, Mikael Lundqvist, Lyle Muller, Matthias Ehrlich, Alain Destexhe, Anders Lansner, René Schüffny, Johannes Schemmel, Karlheinz Meier:
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. CoRR abs/1404.7514 (2014) - 2013
- [j47]Bernhard A. Kaplan, Anders Lansner
Anisotropic connectivity implements motion-based prediction in a spiking neural network. Frontiers Comput. Neurosci. 7: 112 (2013) - [j46]Mikael Lundqvist
Stimulus detection rate and latency, firing rates and 1-40 Hz oscillatory power are modulated by infra-slow fluctuations in a bistable attractor network model. NeuroImage 83: 458-471 (2013) - 2011
- [j45]Daniel Brüderle, Mihai A. Petrovici
A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems. Biol. Cybern. 104(4-5): 263-296 (2011) - [j44]David Silverstein
Is Attentional Blink a Byproduct of Neocortical Attractors? Frontiers Comput. Neurosci. 5: 13 (2011) - [j43]Mikael Lundqvist
Theta and Gamma Power Increases and Alpha/Beta Power Decreases with Memory Load in an Attractor Network Model. J. Cogn. Neurosci. 23(10): 3008-3020 (2011) - [c10]Jordi Fonollosa
Biologically Inspired Computation for Chemical Sensing. FET 2011: 226-227 - 2010
- [j42]Mikael Lundqvist
Bistable, Irregular Firing and Population Oscillations in a Modular Attractor Memory Network. PLoS Comput. Biol. 6(6) (2010)
2000 – 2009
- 2009
- [j41]Christopher Johansson, Anders Lansner:
Implementing plastic weights in neural networks using low precision arithmetic. Neurocomputing 72(4-6): 968-972 (2009) - [j40]Malin Sandström, Anders Lansner
Modeling the response of a population of olfactory receptor neurons to an odorant. J. Comput. Neurosci. 27(3): 337-355 (2009) - 2008
- [j39]Mikael Djurfeldt, Örjan Ekeberg
Large-scale modeling - a tool for conquering the complexity of the brain. Frontiers Neuroinformatics 2: 1 (2008) - [j38]Mikael Djurfeldt, Mikael Lundqvist
Brain-scale simulation of the neocortex on the IBM Blue Gene/L supercomputer. IBM J. Res. Dev. 52(1-2): 31-42 (2008) - 2007
- [j37]Alexander K. Kozlov, Anders Lansner
A hemicord locomotor network of excitatory interneurons: a simulation study. Biol. Cybern. 96(2): 229-243 (2007) - [j36]Malin Sandström, Jeanette Hellgren Kotaleski, Anders Lansner:
Scaling effects in a model of the olfactory bulb. Neurocomputing 70(10-12): 1802-1807 (2007) - [j35]Romain Brette
Simulation of networks of spiking neurons: A review of tools and strategies. J. Comput. Neurosci. 23(3): 349-398 (2007) - [j34]Christopher Johansson, Anders Lansner
Imposing Biological Constraints onto an Abstract Neocortical Attractor Network Model. Neural Comput. 19(7): 1871-1896 (2007) - [j33]Christopher Johansson, Anders Lansner
Towards cortex sized artificial neural systems. Neural Networks 20(1): 48-61 (2007) - 2006
- [j32]Christopher Johansson, Örjan Ekeberg
Clustering of Stored Memories in an Attractor Network with Local Competition. Int. J. Neural Syst. 16(6): 393-404 (2006) - [j31]Christopher Johansson, Martin Rehn, Anders Lansner:
Attractor neural networks with patchy connectivity. Neurocomputing 69(7-9): 627-633 (2006) - [j30]Malin Sandström, Johannes Hjorth
The impact of the distribution of isoforms on CaMKII activation. Neurocomputing 69(10-12): 1010-1013 (2006) - [j29]Mikael Lundqvist
Attractor dynamics in a modular network model of the cerebral cortex. Neurocomputing 69(10-12): 1155-1159 (2006) - [c9]Christopher Johansson, Anders Lansner:
Attractor Memory with Self-organizing Input. BioADIT 2006: 265-280 - [c8]Rebecca Steinert, Martin Rehn, Anders Lansner:
Recognition of handwritten digits using sparse codes generated by local feature extraction methods. ESANN 2006: 161-166 - 2005
- [j28]Baran Çürüklü, Anders Lansner:
A model of the summation pools within the layer 4 (area 17). Neurocomputing 65-66: 167-172 (2005) - [c7]Christopher Johansson, Martin Rehn, Anders Lansner:
Attractor neural networks with patchy connectivity. ESANN 2005: 429-434 - 2004
- [j27]Martin Rehn, Anders Lansner:
Sequence memory with dynamical synapses. Neurocomputing 58-60: 271-278 (2004) - [c6]Christopher Johansson, Anders Lansner:
Towards Cortex Sized Attractor ANN. BioADIT 2004: 63-79 - [c5]Christopher Johansson, Anders Lansner:
Towards Cortex Sized Artificial Nervous Systems. KES 2004: 959-966 - 2003
- [j26]David Eriksson, Erik Fransén, Yuri Zilberter, Anders Lansner:
Effects of short-term synaptic plasticity in a local microcircuit on cell firing. Neurocomputing 52-54: 7-12 (2003) - [j25]Alexander K. Kozlov, Anders Lansner, Sten Grillner:
Burst dynamics under mixed NMDA and AMPA drive in the models of the lamprey spinal CPG. Neurocomputing 52-54: 65-71 (2003) - [j24]Mikael Huss, Dietmar Hess, Boris Lamotte d'Incamps, Abdeljabbar El Manira, Anders Lansner, Jeanette Hellgren Kotaleski:
Role of A-current in lamprey locomotor network neurons. Neurocomputing 52-54: 295-300 (2003) - [j23]Anders Lansner, Erik Fransén, Anders Sandberg:
Cell assembly dynamics in detailed and abstract attractor models of cortical associative memory. Theory Biosci. 122(1): 19-36 (2003) - 2002
- [j22]Alexander K. Kozlov, Fredrik Ullén, Patriq Fagerstedt
Mechanisms for lateral turns in lamprey in response to descending unilateral commands: a modeling study. Biol. Cybern. 86(1): 1-14 (2002) - [j21]Anders Sandberg, Anders Lansner:
Synaptic depression as an intrinsic driver of reinstatement dynamics in an attractor network. Neurocomputing 44-46: 615-622 (2002) - [c4]Christopher Johansson, Anders Sandberg, Anders Lansner:
Attractor Neural Networks with Hypercolumns. ICANN 2002: 192-197 - 2001
- [j20]Niclas Wahlgren, Anders Lansner:
Biological evaluation of a Hebbian-Bayesian learning rule. Neurocomputing 38-40: 433-438 (2001) - [j19]Anders Sandberg, Anders Lansner, Karl Magnus Petersson
Selective enhancement of recall through plasticity modulation in an autoassociative memory. Neurocomputing 38-40: 867-873 (2001) - [j18]Alexander K. Kozlov, Jeanette Hellgren Kotaleski
Modeling of Substance P and 5-HT Induced Synaptic Plasticity in the Lamprey Spinal CPG: Consequences for Network Pattern Generation. J. Comput. Neurosci. 11(2): 183-200 (2001) - [c3]Baran Çürüklü, Anders Lansner:
Spike and Burst Synchronization in a Detailed Cortical Network Model with I-F Neurons. ICANN 2001: 1095-1102 - 2000
- [j17]Alexander K. Kozlov, Jeanette Hellgren Kotaleski, Erik Aurell, Sten Grillner, Anders Lansner:
Modeling of plasticity of the synaptic connections in the lamprey spinal CPG - consequences for network behavior. Neurocomputing 32-33: 441-446 (2000) - [j16]Anders Sandberg, Anders Lansner, Karl Magnus Petersson
A palimpsest memory based on an incremental Bayesian learning rule. Neurocomputing 32-33: 987-994 (2000) - [c2]Anders Lansner, Anders Sandberg, Karl Magnus Petersson, Martin Ingvar:
On Forgetful Attractor Network Memories. ANNIMAB 2000: 54-62
1990 – 1999
- 1999
- [j15]Jeanette Hellgren Kotaleski
Neural mechanisms potentially contributing to the intersegmental phase lag in lamprey. Biol. Cybern. 81(4): 299-315 (1999) - [j14]Jeanette Hellgren Kotaleski
Neural mechanisms potentially contributing to the intersegmental phase lag in lamprey. Biol. Cybern. 81(4): 317-330 (1999) - [j13]Jeanette Hellgren Kotaleski, Jesper Tegnér, Sten Grillner, Anders Lansner:
Control of burst proportion and frequency range by drive-dependent modulation of adaptation. Neurocomputing 26-27: 185-191 (1999) - [j12]Mikael Djurfeldt, Anders Sandberg, Örjan Ekeberg
See - A framework for simulation of biologically detailed and artificial neural networks and systems. Neurocomputing 26-27: 997-1003 (1999) - 1998
- [j11]Guang Li, Anders Lansner, Bertil Svensson:
Self-Orienting with On-Line Learning of Environmental Features. Adapt. Behav. 6(3-4): 535-566 (1998) - [j10]M. Ullström, Jeanette Hellgren Kotaleski
Activity-dependent modulation of adaptation produces a constant burst proportion in a model of the lamprey spinal locomotor generator. Biol. Cybern. 79(1): 1-14 (1998) - [j9]Jesper Tegnér, Anders Lansner
Modulation of Burst Frequency by Calcium-Dependent Potassium Channels in the Lamprey Locomotor System: Dependence of the Activity Level. J. Comput. Neurosci. 5(2): 121-140 (1998) - 1997
- [j8]Tom Wadden
Intersegmental coordination in the lamprey: simulations using a network model without segmental boundaries. Biol. Cybern. 76(1): 1-9 (1997) - [c1]Anders Lansner, Erik Fransén:
Attractor Network Models of Cortical Associative Memory. BCEC 1997: 238-250 - 1996
- [j7]Anders Lansner, Anders Holst:
A Higher order Bayesian Neural Network with Spiking Units. Int. J. Neural Syst. 7(2): 115-128 (1996) - 1995
- [j6]Örjan Ekeberg
The Neural Control of Fish Swimming Studied Through Numerical Simulations. Adapt. Behav. 3(4): 363-384 (1995) - 1993
- [j5]Anders Holst, Anders Lansner:
A Flexible And Fault Tolerant Query-Reply System Based On A Bayesian Neural Network. Int. J. Neural Syst. 4(3): 257-267 (1993) - 1992
- [j4]Jeanette Hellgren
Computer simulation of the segmental neural network generating locomotion in lamprey by using populations of network interneurons. Biol. Cybern. 68(1): 1-13 (1992) - 1991
- [j3]Örjan Ekeberg
A computer based model for realistic simulations of neural networks. Biol. Cybern. 65(2): 81-90 (1991)
1980 – 1989
- 1989
- [j2]Anders Lansner, Örjan Ekeberg:
A One-Layer Feedback Artificial Neural Network with a Bayesian Learning Rule. Int. J. Neural Syst. 1(1): 77-87 (1989) - 1985
- [j1]Anders Lansner, Örjan Ekeberg:
Reliability and Speed of Recall in an Associative Network. IEEE Trans. Pattern Anal. Mach. Intell. 7(4): 490-498 (1985)
Coauthor Index
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