Category: Deep learning

DeepMind Technologies is a British artificial intelligence subsidiary of Alphabet Inc. and research laboratory founded in 2010. DeepMind was acquired by Google in 2014 and became a wholly owned subsid
Knowledge distillation
In machine learning, knowledge distillation is the process of transferring knowledge from a large model to a smaller one. While large models (such as very deep neural networks or ensembles of many mod
Deep learning
Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervi
Deep learning in photoacoustic imaging
Deep learning in photoacoustic imaging combines the hybrid imaging modality of photoacoustic imaging (PA) with the rapidly evolving field of deep learning. Photoacoustic imaging is based on the photoa
Physics-informed neural networks
Physics-informed neural networks (PINNs) are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can
Large memory storage and retrieval neural network
A large memory storage and retrieval neural network (LAMSTAR) is a fast deep learning neural network of many layers that can use many filters simultaneously. These filters may be nonlinear, stochastic
CLEVER score
The CLEVER (Cross Lipschitz Extreme Value for nEtwork Robustness) score is a way of measuring the robustness of an artificial neural network towards adversarial attacks.It was developed by a team at t
Large width limits of neural networks
Artificial neural networks are a class of models used in machine learning, and inspired by biological neural networks. They are the core component of modern deep learning algorithms. Computation in ar
Region Based Convolutional Neural Networks
Region-based Convolutional Neural Networks (R-CNN) are a family of machine learning models for computer vision and specifically object detection.
Question answering
Question answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP), which is concerned with building systems that automatically a
Neural network Gaussian process
Bayesian networks are a modeling tool for assigning probabilities to events, and thereby characterizing the uncertainty in a model's predictions. Deep learning and artificial neural networks are appro
Neural style transfer
Neural style transfer (NST) refers to a class of software algorithms that manipulate digital images, or videos, in order to adopt the appearance or visual style of another image. NST algorithms are ch
Digital cloning
Digital cloning is an emerging technology, that involves deep-learning algorithms, which allows one to manipulate currently existing audio, photos, and videos that are hyper-realistic. One of the impa
Dilution (neural networks)
Dilution and dropout (also called DropConnect) are regularization techniques for reducing overfitting in artificial neural networks by preventing complex co-adaptations on training data. They are an e
DL Boost
Intel's Deep Learning Boost (DL Boost) is a marketing name for instruction set architecture features on the x86-64 designed to improve performance on deep learning tasks such as training and inference
Hierarchical temporal memory
Hierarchical temporal memory (HTM) is a biologically constrained machine intelligence technology developed by Numenta. Originally described in the 2004 book On Intelligence by Jeff Hawkins with Sandra
Deep learning processor
A deep learning processor (DLP), or a deep learning accelerator, is an electronic circuit designed for deep learning algorithms, usually with separate data memory and dedicated instruction set archite
Deep image prior
Deep image prior is a type of convolutional neural network used to enhance a given image with no prior training data other than the image itself.A neural network is randomly initialized and used as pr
Conversica is a US-based cloud software technology company, headquartered in Silicon Valley, (Foster City, California) that provides AI-driven lead engagement software for marketing and sales organiza
Artificial intelligence in fraud detection
Artificial intelligence is used by many different businesses and organizations. It is widely used in the financial sector, especially by accounting firms, to help detect fraud. In 2022, Pricewaterhous
Foundation models
A foundation model is a large artificial intelligence model trained on a vast quantity of unlabeled data at scale (usually by self-supervised learning) resulting in a model that can be adapted to a wi
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 problem of a computational agent learning to make
Netomi, formerly, is an American artificial intelligence company and developer of human–computer interaction technologies.
Deepfakes (a portmanteau of "deep learning" and "fake") are synthetic media in which a person in an existing image or video is replaced with someone else's likeness. While the act of creating fake con
Deep Instinct
Deep Instinct is a cybersecurity company that applies deep learning to cybersecurity. The company implements advanced artificial intelligence to the task of preventing and detecting malware. The compa
Multi-agent reinforcement learning
Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that coexist in a shared environment. Each agent is