Flux is an open-source machine-learning software library and ecosystem written in Julia. Its current stable release is v0.15.0 . It has a layer-stacking-based...

on certain trees Flux (machine-learning framework) Flux (graphics software), a suite of VRML/X3D viewing/authoring software Flux (software company), a...

in machine learning: a survey". arXiv:1502.05767 [cs.LG]. "Microsoft/caffe". GitHub. 30 October 2021. "Caffe: a fast open framework for deep learning"....

libraries, frameworks, platforms, and tools used for machine learning, deep learning, natural language processing, computer vision, reinforcement learning, artificial...

of Functional Connections (X-TFC) framework, where a single-layer Neural Network and the extreme learning machine training algorithm are employed. X-TFC...

Quantum machine learning (QML) is the study of quantum algorithms which solve machine learning tasks. The most common use of the term refers to quantum...

(TensorFlow), Deep Graph Library (framework agnostic), jraph (Google JAX), and GraphNeuralNetworks.jl/GeometricFlux.jl (Julia, Flux). The architecture of a generic...

Guttag, John (November 4, 2021). "A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle". Equity and Access in Algorithms...

computing and machine learning. One of the early proposals to adopt such a framework in a systematic fashion to improve upon learning algorithms was...

Wayback Machine "FlightCaster". "Ion Flux". Archived from the original on October 23, 2011. RapLeaf Blog Archived February 1, 2011, at the Wayback Machine "Razorfish...

deep-learning library for Python with an API largely compatible with the NumPy library. Torch: A scientific computing framework with support for machine learning...

use machine learning algorithms to build predictive models. Data science often uses statistical analysis, data preprocessing, and supervised learning. Cloud...

Applying machine learning (ML) (including deep learning) methods to the study of quantum systems is an emergent area of physics research. A basic example...

Sparse dictionary learning (also known as sparse coding or SDL) is a representation learning method which aims to find a sparse representation of the input...

engineering, which involves the selection of features that are fed into machine learning algorithms, plays a key role in the sentiment classification performance...

machines can be related to classical and probabilistic Turing machines in a framework based on transition matrices. That is, a matrix can be specified...

optimised using methods from quantum machine learning to solve data-driven tasks such as question answering, machine translation and even algorithmic music...

some express hope in developing quantum algorithms that can speed up machine learning tasks. For example, the HHL Algorithm, named after its discoverers...

efficient machine learning models, minimizing the number of times that models need to be retrained, developing a government-directed framework for auditing...

announced at the International Workshop on Quantum Software and Quantum Machine Learning on July 18, 2018. A demo by QC Ware showed an implementation of QAOA...

quantitative psychology, machine learning, artificial neural networks, artificial intelligence and computational learning theory; although mutual inspiration...

discriminant, a method used in statistics, pattern recognition, and machine learning to find a linear combination of features that characterizes or separates...

quantum computing attacks. Mosca's theorem provides the risk analysis framework that helps organizations identify how quickly they need to start migrating...

augmented reality". pwc. Pereira, Fernando. "Deep Learning-Based Extended Reality: Making Humans and Machines Speak the Same Visual Language." In Proceedings...

classical artificial neural network models (which are widely used in machine learning for the important task of pattern recognition) with the advantages...

1007/978-3-642-12929-2_6. ISBN 978-3-642-12928-5. Grover, Lov K. (1998). "A framework for fast quantum mechanical algorithms". In Vitter, Jeffrey Scott (ed...

total magnetic flux through that loop. This has been used on the National Compact Stellarator Experiment, the polywell, and the LDX machines. A Langmuir...

Retrieved March 26, 2021. "AWS joins PennyLane, an open-source framework that melds machine learning with quantum computing". SiliconANGLE. February 17, 2021...

studies include methods for solving Schrödinger's or Dirac's equation, machine learning equations, among others. These methods include the development of computational...

Deinum, Marten; Cosmina, Iuliana (2021), "Spring Framework Fundamentals", Pro Spring MVC with WebFlux, Berkeley, CA: Apress, pp. 21–54, ISBN 978-1-4842-5665-7...