Andreas Knoblauch
2 indexed papers
Recent (6 mo)
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226
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Neural Computing×2ML×1
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2026
Supervised Hebbian learning in Deep Counterstream Associative Networks
A new error backpropagation method called supervised counterstream learning is proposed for deep associative networks, which only requires recognition of errors during training and backpropagates correcting target activity through the same activity channel as used for forward propagation.
Constrained Hebbian Learning Supports Efficient Representational Allocation under Structural Constraints
This paper compares the cost-performance trade-off of Hebbian learning, Dense Difference Target Propagation (DDTP), and backpropagation (BP) using mutual-information-based measures.
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Papers
cs.LGcs.NEEmpiricalRecentJul 17, 2026
Constrained Hebbian Learning Supports Efficient Representational Allocation under Structural Constraints
This paper compares the cost-performance trade-off of Hebbian learning, Dense Difference Target Propagation (DDTP), and backpropagation (BP) using mutual-information-based measures.
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cs.NEEmpirical