Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation...

Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the...

A transformer is a deep learning architecture that was developed by researchers at Google and is based on the multi-head attention mechanism, which was...

Deep learning super sampling (DLSS) is a family of real-time deep learning image enhancement and upscaling technologies developed by Nvidia that are available...

Topological deep learning (TDL) is a research field that extends deep learning to handle complex, non-Euclidean data structures. Traditional deep learning models...

"Deep Learning" is the fourth episode of the twenty-sixth season of the American animated television series South Park, and the 323rd episode of the series...

An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator or computer system designed...

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...

compare notable software frameworks, libraries, and computer programs for deep learning applications. Licenses here are a summary, and are not taken to be complete...

perform tasks without explicit instructions. Advances in the field of deep learning have allowed neural networks to surpass many previous approaches in...

"Provable Bounds for Learning Some Deep Representations". Proceedings of the 31st International Conference on Machine Learning. PMLR: 584–592. Szegedy...

Q-learning algorithm. In 2014, Google DeepMind patented an application of Q-learning to deep learning, titled "deep reinforcement learning" or "deep Q-learning"...

Mamba is a deep learning architecture focused on sequence modeling. It was developed by researchers from Carnegie Mellon University and Princeton University...

In deep learning, fine-tuning is an approach to transfer learning in which the parameters of a pre-trained neural network model are trained on new data...

Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Q-learning at its simplest...

Deep learning anti-aliasing (DLAA) is a form of spatial anti-aliasing created by Nvidia. DLAA depends on and requires Tensor Cores available in Nvidia...

In U.S. education, deeper learning is a set of student educational outcomes including acquisition of robust core academic content, higher-order thinking...

A layer in a deep learning model is a structure or network topology in the model's architecture, which takes information from the previous layers and...

as AI winters. Funding and interest vastly increased after 2012 when deep learning outperformed previous AI techniques. This growth accelerated further...

features by itself via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different...

Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech)...

Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images...

launched the ongoing AI spring, and further increasing interest in deep learning. The transformer architecture was first described in 2017 as a method...

artificial intelligence and deep learning; including self-driving cars, healthcare, high-performance computing, and Nvidia Deep Learning Institute (DLI) training...

Google Brain was a deep learning artificial intelligence research team that served as the sole AI branch of Google before being incorporated under the...

things, and pharmaceuticals. Federated learning aims at training a machine learning algorithm, for instance deep neural networks, on multiple local datasets...

deep learning software. On August 9, 2016, it was acquired by Intel, for an estimated $408 million. The company's (now discontinued) open-source deep...

In deep learning, a multilayer perceptron (MLP) is a name for a modern feedforward neural network consisting of fully connected neurons with nonlinear...

chess) after a few days of play against itself using reinforcement learning. In 2020, DeepMind made significant advances in the problem of protein folding...

Deepfakes (a portmanteau of 'deep learning' and 'fake') are images, videos, or audio which are edited or generated using artificial intelligence tools...