Think like a brain!
Neuromorphic means brain-inspired; this is a growing field that aims to learn lessons from the efficient processing and computation of biological brains. This group aims to facilitate collaboration between those who study brains, algorithms, and engineering by providing a semi-formal environment to share new research articles and ideas.
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From Luis El Srouji
Abstract: Despite their seemingly impressive performance at image recognition and other perceptual tasks, deep convolutional neural networks are prone to be easily… -
From Luis El Srouji
Abstract: Flexible function is essential for the brain to cope with varying environments, changing quality of sensory information as well as context dependency. This… -
From Luis El Srouji
Abstract: As Moore’s Law comes to a close, new innovative approaches to microelectronics research are important to achieve much needed capabilities improvements… -
From Luis El Srouji
Prof. Cawenberghs presents neuromorphic cognitive computing systems-on-chip implemented in custom silicon compute-in-memory neural and memristive synaptic crossbar array… -
From Luis El Srouji
Discussion of analog CMOS computation and parallels to biological neurons. Prof. Hasler points out that the exponential voltage controls found in MOS devices can be used… -
From Luis El Srouji
Luis El Srouji leads a discussion on Vector Symbolic Architectures (VSA). VSAs are a mathematical framework in which basis vectors encode some attribute (color, weight,… -
From Luis El Srouji
Professor Olshausen discusses the neural circuits thought to underly signal compression in the retina, and theories of attractor dynamics downstream in cortex that may… -
From Luis El Srouji
Professor Chris Eliasmith gave a guest presentation on some mechanisms of encoding information within spiking neural networks. Spatial Semantic Pointers are an extension… -
From Luis El Srouji
Algorithmic Frameworks for Neuromorphic Computing: Neural Engineering Framework (NEF) Luis El Srouji gives an overview and explanation of the Neural Engineering… -
From Luis El Srouji
Mehmet Berkay leads a discussion on the potential biological basis for backpropagation and a justification for its uses in spiking neural networks. -
From Luis El Srouji
Dr. Farhad Shokraneh goes over his recent work on an optical processor for neural networks, and describes the features which make this architecture more fault- and… -
From Luis El Srouji
Quick video introducing our group's use of Microsoft Teams and how to join. -
From Luis El Srouji
Professor Randy O'Reilly presented on Predictive Error-Driven Learning in the Brain; this method approximates backpropagation in rate-approximated neural networks… -
From Luis El Srouji
A review of basic neurobiology followed by a discussion on the capabilities of IBM's TrueNorth and Intel's Loihi neuromorphic chips. -
From Luis El Srouji
First club meeting; a brief overview of neuromorphic computing in comparison to both biological brains and Von Neumann computers. A short discussion of ABR's Nengo…