PinnedPublished inTDS ArchiveAIKA: An event-driven neural network architectureEvent-Queues as an efficient way to process sparsely populated input data sets such as text efficiently.Feb 14, 2021Feb 14, 2021
Event-Driven Programming vs. Differential AlgebraAre the event-driven programming paradigm and differential algebra two sides of the same coin?Mar 25, 20222Mar 25, 20222
Published inTDS ArchiveCan the dynamic linking of neural activations bring us closer to strong AI?Most artificial neural networks ignore the spiking nature of biological neural networks to simplify the underlying model and enable…Jan 1, 20202Jan 1, 20202
Published inTDS ArchiveUsing Information Gain for the Unsupervised Training of Excitatory NeuronsLooking for a biologically more plausible way to train a neural network.Sep 23, 2019Sep 23, 2019
Published inTDS ArchiveUsing Meta-Neurons to learn facts from a single training exampleWhen people see a new animal, meet a new person or visit a new place, they don’t need to repeat that experience thousands of times to…Aug 28, 20193Aug 28, 20193
Published inTDS ArchiveHow to efficiently propagate activations in a massive neural networkAn event-driven approachAug 9, 2019Aug 9, 2019
Published inTDS ArchiveOn adding negative recurrent synapses to a neural networkThe missing link in deep neural networks.Aug 3, 20191Aug 3, 20191
Published inTDS ArchiveOn integrating symbolic inference into deep neural networksWhat makes biological neural networks so superior to their technical counterparts? Is there anything we have overlooked so far?Dec 9, 2018Dec 9, 2018
