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Found 6 papers, 1 papers with code
Transformers and Cortical Waves: Encoders for Pulling In Context Across Time
The capabilities of transformer networks such as ChatGPT and other Large Language Models (LLMs) have captured the world's attention.
Traveling Waves Encode the Recent Past and Enhance Sequence Learning
Traveling waves of neural activity have been observed throughout the brain at a diversity of regions and scales; however, their precise computational role is still debated.
A unified framework of metastability in neuroscience
Neural activity typically follows a series of transitions between well-defined states, in a regime generally called metastability.
An algebraic approach to spike-time neural codes in the hippocampus
Here, we introduce a new analytical approach, using techniques from discrete mathematics, to study spike-time codes.
An Optimally Weighted Echo State Neural Network for Highly Chaotic Time Series Modelling
We demonstrate the development and implementation of a series of echo state neural networks in conjunction with optimal weighted averaging to produce robust, model-free predictions of highly chaotic time series.
Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms
Advancing the size and complexity of neural network models leads to an ever increasing demand for computational resources for their simulation.
