Artificial intelligence (AI) is rapidly becoming one of the key technolo...
Continuous Ant-based Topology Search (CANTS) is a previously introduced ...
We develop a novel credit assignment algorithm for information processin...
Time series forecasting (TSF) is one of the most important tasks in data...
We propose the predictive forward-forward (PFF) algorithm for conducting...
In this work, we develop convolutional neural generative coding (Conv-NG...
The active inference framework (AIF) is a promising new computational
fr...
In this article, we propose a backpropagation-free approach to robotic
c...
We present a new cognitive architecture that combines two neurobiologica...
Recent advances in deep learning have led to superhuman performance acro...
Recent advances in deep learning have resulted in image compression
algo...
A lifelong learning agent is able to continually learn from potentially
...
Transformer-based models such as BERT, XLNET, and XLM-R have achieved
st...
In this article, we present a cognitive architecture that is built from
...
Automated mathematical reasoning is a challenging problem that requires ...
Neural generative models can be used to learn complex probability
distri...
This work introduces a novel, nature-inspired neural architecture search...
Training deep neural networks on large-scale datasets requires significa...
In order to learn complex grammars, recurrent neural networks (RNNs) req...
For energy-efficient computation in specialized neuromorphic hardware, w...
In lifelong learning systems, especially those based on artificial neura...
This paper presents a new algorithm, Evolutionary eXploration of Augment...
This paper presents a new algorithm, Evolutionary eXploration of Augment...
Temporal models based on recurrent neural networks have proven to be qui...
Temporal models based on recurrent neural networks have proven to be qui...