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12/31/2021
Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments
A key challenge for AI is to build embodied systems that operate in dyna...
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12/27/2021
Two Sparsities Are Better Than One: Unlocking the Performance Benefits of Sparse-Sparse Networks
In principle, sparse neural networks should be significantly more effici...
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02/17/2021
Grid Cell Path Integration For Movement-Based Visual Object Recognition
Grid cells enable the brain to model the physical space of the world and...
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12/02/2019
Long Distance Relationships without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling
In sequence learning tasks such as language modelling, Recurrent Neural ...
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03/27/2019
How Can We Be So Dense? The Benefits of Using Highly Sparse Representations
Most artificial networks today rely on dense representations, whereas bi...
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07/08/2016
Real-Time Anomaly Detection for Streaming Analytics
Much of the worlds data is streaming, time-series data, where anomalies ...
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01/05/2016
How do neurons operate on sparse distributed representations? A mathematical theory of sparsity, neurons and active dendrites
We propose a formal mathematical model for sparse representations and ac...
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12/17/2015
Continuous online sequence learning with an unsupervised neural network model
The ability to recognize and predict temporal sequences of sensory input...
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10/31/2015
Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex
Neocortical neurons have thousands of excitatory synapses. It is a myste...
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10/12/2015
Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark
Much of the world's data is streaming, time-series data, where anomalies...
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05/08/2015
Porting HTM Models to the Heidelberg Neuromorphic Computing Platform
Hierarchical Temporal Memory (HTM) is a computational theory of machine ...
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03/25/2015