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Interdisciplinary research area
Quantum machine learning (QML) is the study of quantum algorithms for machine learning. It often refers to quantum algorithms for machine learning tasks
Quantum_machine_learning
Process of automating the application of machine learning
Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. It is the combination
Automated_machine_learning
Machine learning technique
In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence
Attention_(machine_learning)
Model of quantum computation
A quantum Turing machine (QTM) or universal quantum computer is an abstract machine used to model the effects of a quantum computer. It provides a simple
Quantum_Turing_machine
Computer hardware technology that uses quantum mechanics
A quantum computer is a computer that represents and processes information using quantum states. Quantum computations exploit phenomena such as superposition
Quantum_computing
Applications of machine learning to quantum physics
Applying machine learning (ML) (including deep learning) methods to the study of quantum systems is an emergent area of physics research. A basic example
Machine_learning_in_physics
Machine learning methods using multiple input modalities
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
Multimodal_learning
Academic conference in machine learning
The International Conference on Machine Learning (ICML) is an international academic conference in machine learning held annually since 1980. It is the
International Conference on Machine Learning
International_Conference_on_Machine_Learning
Plot of machine learning model performance over time or experience
In machine learning (ML), a learning curve (or training curve) is a graphical representation that shows how a model's performance on a training set (and
Learning curve (machine learning)
Learning_curve_(machine_learning)
Ensemble learning method
In machine learning (ML), boosting is an ensemble learning method that combines a set of less accurate models (called "weak learners") to create a single
Boosting_(machine_learning)
Machine learning strategy
Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source)
Active learning (machine learning)
Active_learning_(machine_learning)
Measurable property or characteristic
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. Choosing informative, discriminating
Feature_(machine_learning)
Quantum mechanical macroscopic object
A quantum machine is a human-made device whose collective motion follows the laws of quantum mechanics. The idea that macroscopic objects may follow the
Quantum_machine
Canadian physicist and entrepreneur
quantum computing researcher, entrepreneur, and writer who is a key contributor of Google's quantum machine learning software, Tensorflow Quantum. He
Guillaume_Verdon
Subset of artificial intelligence
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn
Machine_learning
Concept in machine learning
In statistics and machine learning, leakage (also known as data leakage or target leakage) refers to the use of information during model training that
Leakage_(machine_learning)
Academic conference in machine learning
The International Conference on Learning Representations (ICLR) is a machine learning conference typically held in late April or early May each year.
International Conference on Learning Representations
International_Conference_on_Learning_Representations
Machine learning technique
Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related
Transfer_learning
Research field that lies at the intersection of machine learning and computer security
Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. Machine learning techniques
Adversarial_machine_learning
Statistics and machine learning technique
In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from
Ensemble_learning
Interdisciplinary theory behind quantum computing
Quantum information science is an interdisciplinary field that combines the principles of quantum mechanics, information theory, and computer science
Quantum_information_science
Fact that observing a situation changes it
effect occurs in quantum mechanics, as demonstrated by the double-slit experiment. Physicists have found that observation of quantum phenomena by a detector
Observer_effect_(physics)
Computing company founded in 2014
quantum chemistry, quantum machine learning, quantum Monte Carlo integration, and quantum artificial intelligence. The company also offers quantum-computing-hardened
Quantinuum
Quantum computing company based in Toronto, Canada
cloud accessible photonic quantum computers and develops open-source software for quantum machine learning and simulating quantum photonic devices. Xanadu
Xanadu_Quantum_Technologies
Machine learning technique
In machine learning, normalization is a statistical technique with various applications. There are two main forms of normalization, namely data normalization
Normalization (machine learning)
Normalization_(machine_learning)
Overview of and topical guide to machine learning
outline is provided as an overview of, and topical guide to, machine learning: Machine learning (ML) is a subfield of artificial intelligence within computer
Outline_of_machine_learning
Set of methods for supervised statistical learning
In machine learning, a support vector machine (SVM) or support vector network is a supervised max-margin model with associated learning algorithms that
Support_vector_machine
Type of large language model
the problem before generating an output. During the 2010s, improved machine learning algorithms, more powerful computers, and an increase in the amount
Generative pre-trained transformer
Generative_pre-trained_transformer
Technological development using the laws of quantum mechanics
qubits, and others. Quantum machine learning has also been proposed. Two examples of this are quantum clustering, where quantum principles might be used
Quantum_engineering
Quantum algorithm
found applications in quantum machine learning and has been further substantiated by general hybrid algorithms between quantum and classical computers
Variational quantum eigensolver
Variational_quantum_eigensolver
Machine learning paradigm using minimal training data
Few-shot learning (FSL) is a problem setup in machine learning in which a model learns to perform a task, typically classification, from only a small
Few-shot_learning
development of quantum computing, quantum communication and quantum sensing. Quantum computing and communication are two sub-fields of quantum information
List of companies involved in quantum computing, communication or sensing
List_of_companies_involved_in_quantum_computing,_communication_or_sensing
Algorithm for modelling sequential data
In deep learning, the transformer is a family of artificial neural network architectures based on the multi-head attention mechanism, in which text is
Transformer_(deep_learning)
Area of physical and philosophical debate
interpretation of quantum mechanics is an attempt to explain how the mathematical theory of quantum mechanics might correspond to experienced reality. Quantum mechanics
Interpretations of quantum mechanics
Interpretations_of_quantum_mechanics
Machine learning method
Logic learning machine (LLM) is a machine learning method based on the generation of intelligible rules. LLM is an efficient implementation of the Switching
Logic_learning_machine
AI that learns decision rules from data
Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves
Rule-based_machine_learning
Phenomenon resulting from the superposition of two waves
addition to the classical wave model for understanding optical interference, quantum matter waves also demonstrate interference. The above can be demonstrated
Wave_interference
Academic journal
The Journal of Machine Learning Research is a peer-reviewed open access scientific journal covering machine learning. It was established in 2000 and the
Journal of Machine Learning Research
Journal_of_Machine_Learning_Research
Cryptography secured against quantum computers
Post-quantum cryptography (PQC), sometimes referred to as quantum-proof, quantum-safe, or quantum-resistant, is the development of cryptographic algorithms
Post-quantum_cryptography
Process in quantum computing
Quantum error correction (QEC) comprises a set of techniques used in quantum memory and quantum computing to protect quantum information from errors arising
Quantum_error_correction
American mathematical physicist (born 1979)
adiabatic quantum computation and the universality of variational quantum computation. His work also includes contributions to quantum machine learning and
Jacob_Biamonte
Quantum computing applied to natural language processing
answering, machine translation and even algorithmic music composition. Categorical quantum mechanics Natural language processing Quantum machine learning Applied
Quantum natural language processing
Quantum_natural_language_processing
Principle of quantum mechanics
Quantum superposition is a fundamental principle of quantum mechanics that states that linear combinations of solutions to the Schrödinger equation are
Quantum_superposition
Framework for machine learning
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. Statistical learning theory
Statistical_learning_theory
Networks connecting quantum processors
form of quantum bits, also called qubits, between physically separated quantum processors. A quantum processor is a machine able to perform quantum circuits
Quantum_network
Quantum Mechanics in Neural Networks
models (which are widely used in machine learning for the important task of pattern recognition) with the advantages of quantum information in order to develop
Quantum_neural_network
Branch of physics seeking to explain chaotic dynamical systems in terms of quantum theory
little about quantum chaos. Nevertheless, learning how to solve such quantum problems is an important part of answering the question of quantum chaos. Statistical
Quantum_chaos
Algorithm to be run on quantum computers
In quantum computing, a quantum algorithm is an algorithm that runs on a realistic model of quantum computation, the most commonly used model being the
Quantum_algorithm
Machine learning calibration technique
In machine learning, Platt scaling or Platt calibration is a way of transforming the outputs of a classification model into a probability distribution
Platt_scaling
Canadian economist
Lab added a machine learning and artificial intelligence (AI) stream. In 2017, the CDL launched a program focused on quantum machine learning. Agrawal is
Ajay_Agrawal
Machine learning technique
In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves
Reinforcement learning from human feedback
Reinforcement_learning_from_human_feedback
Class of theories in quantum mechanics
In quantum mechanics, superdeterminism is a loophole in Bell's theorem. By postulating that all systems being measured are correlated with the choices
Superdeterminism
Method of machine learning
In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update
Online_machine_learning
Technique for the generative modeling of a continuous probability distribution
In machine learning, diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable
Diffusion_model
Research field in deep learning
deep learning (TDL) is a research field that extends deep learning to handle complex, non-Euclidean data structures. Traditional deep learning models
Topological_deep_learning
Simulators of quantum mechanical systems
quantum Turing machines are useful for simulating quantum systems. This is known as quantum supremacy, the idea that there are problems only quantum Turing
Quantum_simulator
Model-free reinforcement learning algorithm
Q-learning is a reinforcement learning algorithm that trains an agent to assign values to its possible actions based on its current state, without requiring
Q-learning
Integrated circuit technology
using protons for analog deep learning. In 2019, the European Union funded neuromorphic quantum computing to explore quantum operations using neuromorphic
Neuromorphic_computing
Machine learning paradigm
Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals
Self-supervised_learning
Machine learning algorithm
Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or
Decision_tree_learning
Deep learning architecture
most relevant expert for each token. Language modeling Transformer (machine learning model) State-space model Recurrent neural network Gu, Albert; Dao,
Mamba (deep learning architecture)
Mamba_(deep_learning_architecture)
Theoretical problem in quantum physics
In quantum mechanics, the measurement problem is the problem of definite outcomes: quantum systems have superpositions but quantum measurements only give
Measurement_problem
Force resulting from the quantisation of a field
In quantum field theory, the Casimir effect (or Casimir force) is a physical force acting on the macroscopic boundaries of a confined space which arises
Casimir_effect
Problem setup in machine learning
Zero-shot learning (ZSL) is a problem setup in machine learning where, at test time, a learner observes samples from classes which were not observed during
Zero-shot_learning
Type of feedforward neural network
In deep learning, a multilayer perceptron (MLP) is a kind of modern feedforward neural network consisting of fully connected neurons with nonlinear activation
Multilayer_perceptron
Technique in machine learning
Curriculum learning is a technique in machine learning in which a model is trained on examples of increasing difficulty, where the definition of "difficulty"
Curriculum_learning
Information held in the state of a quantum system
Quantum information is the information of the state of a quantum system. It is the basic entity of study in quantum information science, and can be manipulated
Quantum_information
Computational benchmark
In quantum computing, quantum supremacy or quantum advantage is the goal of demonstrating that a programmable quantum computer can solve a problem that
Quantum_supremacy
Machine learning that combines deep learning and 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
Deep_reinforcement_learning
Machine-learning and computational-neuroscience conference
Processing Systems (abbreviated as NeurIPS and formerly NIPS) is a machine learning and computational neuroscience conference held annually in December
Conference on Neural Information Processing Systems
Conference_on_Neural_Information_Processing_Systems
Optimization algorithm
become an important optimization method in machine learning. Both statistical estimation and machine learning consider the problem of minimizing an objective
Stochastic_gradient_descent
List of software for quantum computing
logic gate Quantum machine learning Quantum neural network Fingerhuth, Mark; Babej, Tomáš; Wittek, Peter (2018). "Open source software in quantum computing"
List_of_quantum_software
2026 act
on emerging technologies, including "artificial intelligence, quantum machine learning and autonomous systems", "directed energy and advanced sensing"
United States-Israel FUTURES Act
United_States-Israel_FUTURES_Act
Interpretation of quantum mechanics
The many-worlds interpretation (MWI) is an interpretation of quantum mechanics that asserts that the universal wave function is objectively real, and
Many-worlds_interpretation
Software user interface
context of machine learning.It is also used in conversational AI to manage complex interactions that require human empathy. In machine learning, HITL is
Human-in-the-loop
German scientist
his contributions to quantum machine learning. He is currently Vice President of Engineering at Google where he leads the Quantum Artificial Intelligence
Hartmut_Neven
Paradigm in machine learning that uses no classification labels
Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled
Unsupervised_learning
Loss of quantum coherence
Quantum decoherence is the loss of quantum coherence. It involves generally a loss of information of a system to its environment. Quantum decoherence
Quantum_decoherence
2018 text-generating language model
primarily employed supervised learning from large amounts of manually labeled data. This reliance on supervised learning limited their use of datasets
GPT-1
Non-mathematical introduction
Quantum mechanics is the study of matter and matter's interactions with energy on the scale of atomic and subatomic particles. By contrast, classical
Introduction to quantum mechanics
Introduction_to_quantum_mechanics
Field of machine learning
Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. While supervised learning and
Reinforcement_learning
NC-using quantum materials with some variety of potential neuromorphic computing-related applications. The use of quantum machine learning for quantum simulators
Applications of artificial intelligence
Applications_of_artificial_intelligence
Branch of mathematics
Quantum calculus, sometimes called calculus without limits, is equivalent to traditional infinitesimal calculus without the notion of limits. The two
Quantum_calculus
Set of learning techniques in machine learning
In machine learning (ML), feature learning or representation learning is a set of techniques that allow a system to automatically discover the representations
Feature_learning
Type of quantum computer
A topological quantum computer is a type of quantum computer. It utilizes anyons, a type of quasiparticle that occurs in two-dimensional systems. The
Topological_quantum_computer
Smooth approximation of one-hot arg max
accurate term "softargmax", though the term "softmax" is conventional in machine learning. This section uses the term "softargmax" for clarity. Formally, instead
Softmax_function
Framework for mathematical analysis of machine learning
computational learning theory, probably approximately correct (PAC) learning is a framework for mathematical analysis of machine learning. It was proposed
Probably approximately correct learning
Probably_approximately_correct_learning
Interpretation of quantum mechanics
philosophy of physics, QBism (pronounced "cubism") is an interpretation of quantum mechanics that takes an agent's actions and experiences as the central
QBism
Theory of machine learning
Theoretical results in machine learning often focus on a type of inductive learning known as supervised learning. In supervised learning, an algorithm is provided
Computational_learning_theory
Physics experiment
In quantum mechanics, a quantum eraser experiment is an interferometer experiment that demonstrates several fundamental aspects of quantum mechanics,
Quantum_eraser_experiment
Model of quantum computing
In quantum information theory, a quantum circuit is a model for quantum computation, similar to classical circuits, in which a computation is a sequence
Quantum_circuit
American computer scientist (born 2000)
of quantum algorithms for machine learning and linear algebra, and for advances in quantum machine learning on quantum data." Tang's father is Liping Tang
Ewin_Tang
Type of artificial neural network
learning machines are feedforward neural networks for classification, regression, clustering, sparse approximation, compression and feature learning with
Extreme_learning_machine
Technique for comparing quantum states
It appears commonly in quantum machine learning, and is a circuit used for proofs-of-concept in implementations of quantum computers. Formally, the
Swap_test
Set of mathematical concepts in quantum gravity
In quantum gravity, quantum geometry is the set of mathematical concepts that generalize geometry to describe physical phenomena at distance scales comparable
Quantum_geometry
Australian quantum computing company
data environment. Quantum computing Cloud-based quantum computing Quantum machine learning Surface science Quantum chemistry Quantum error correction Schofield
Silicon_Quantum_Computing
Physics phenomenon
Quantum entanglement is the phenomenon in which the quantum state of each particle in a group cannot be described independently of the state of the others
Quantum_entanglement
This is a list of notable textbooks on classical mechanics and quantum mechanics arranged according to level and surnames of the authors in alphabetical
List of textbooks on classical mechanics and quantum mechanics
List_of_textbooks_on_classical_mechanics_and_quantum_mechanics
Similarity measure for number sequences
techniques. This normalised form distance is often used within many deep learning algorithms. In biology, there is a similar concept known as the Otsuka–Ochiai
Cosine_similarity
Mathematical entity to describe the probability of each possible measurement on a system
In quantum physics, a quantum state is a mathematical entity that represents a physical system. Quantum mechanics specifies the construction, evolution
Quantum_state
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