Deep learning
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Deep learning
In machine learning, deep learning focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation...
Transformer (deep learning)
In deep learning, the transformer is an artificial neural network architecture based on the multi-head attention mechanism, in which text is converted...
Machine learning
explicit instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed neural networks, a class of statistical...
Deep reinforcement learning
Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the...
Neural network (machine learning)
learning algorithm for hidden units, i.e., deep learning. Fundamental research was conducted on ANNs in the 1960s and 1970s. The first working deep learning...
Deep Learning Super Sampling
Deep Learning Super Sampling (DLSS) is a suite of real-time deep learning image enhancement and upscaling technologies developed by Nvidia that are available...
Reinforcement learning
Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. While supervised learning and...
Mamba (deep learning architecture)
Mamba is a deep learning architecture focused on sequence modeling. It was developed by two researchers Albert Gu from Carnegie Mellon University and...
Convolutional neural network
that learns features via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different...
Topological deep learning
Topological deep learning (TDL) is a research field that extends deep learning to handle complex, non-Euclidean data structures. Traditional deep learning models...