Tag: recurrent neural networks

A published study reports that a Big Bang-Big Crunch optimized Peephole LSTM model classified course records in a 10,000-record dataset ...

A 25-network simulation study found that modeled cortical core–periphery circuits enhance information flux by preventing recurrent cores from becoming saturated, ...

A new study shows that Dale's principle and modular connectivity boost the computational performance of recurrent neural networks, while Hopfield-style ...

Chronic stress has become one of the defining health burdens of the modern era, quietly fueling hypertension, depression, burnout, and ...

Researchers propose combining deep learning with organism-based ecology and new sensory instruments to build AI models capable of forecasting how ...

A comparative study of three deep learning models in an Australian alpine catchment shows that LSTM networks can forecast hourly ...

Researchers have developed a self-tuning zeroing neural network with a dynamic adaptive gain and integral activation function that lets multi-agent ...

A new theoretical study shows that noise-like fluctuations in neural activity can shift the spectral knee and 1/f power spectrum ...

A new dendrite-inspired recurrent neural network architecture outperforms LSTMs on chaotic forecasting benchmarks and achieves strong seizure detection in raw ...

Researchers at the University of Tokyo show that a single recurrent spiking neural network can learn event identity, timing, and ...