27,049 technical terms and definitions
Magnon Torque Spintronics, Spin-Wave Momentum Transfer, LLGS Dynamics, and All-Magnonic Logic 1. Introduction: Spin-Orbit Coupling and Spintronics Spin-orbit coupling (SOC) is…
magnonic computing and circuits, magnonic computing circuits, magnonic computing, computing circuits
Magnonic Computing and Circuits Introduction & Motivation Magnonic Computing and Circuits addresses a central problem in magnonic-computing process control and magnon-latency…
Magnonics and Spin-Wave Processing: Dispersion Relations in Yttrium Iron Garnet, Exchange-Dipole Coupling, and All-Magnonic Logic 1. Introduction: Magnonics as an Alternative…
spin wave dispersion relation magnon hamiltonian landau lifshitz, yttrium iron garnet YIG low damping spin wave propagation, magnonic crystal band gap spin wave waveguide
Magnonics and Spin-Wave Processing: Dispersion Relations in Yttrium Iron Garnet, Exchange-Dipole Coupling, and All-Magnonic Logic 1. Introduction: Magnonics as an Alternative…
Magnonics and Spin Wave Dynamics: Dipole-Exchange Dispersion in YIG, Magnonic Crystals, and On-Chip Microwave Waveguides 1. Introduction to Magnonics and Spin-Wave Processing…
Mahalanobis Distance Anomaly Detection Introduction & Motivation Mahalanobis Distance Anomaly Detection addresses a central problem in anomaly detection and {target} scoring: how…
Robust Mahalanobis Distance with Shrinkage Covariance Introduction & Motivation Robust Mahalanobis Distance with Shrinkage Covariance addresses a central problem in anomaly…
Mahalanobis Distance in Deep Feature Space for OOD Introduction & Motivation Mahalanobis Distance in Deep Feature Space for OOD addresses a central problem in anomaly detection…
reasoning
Maieutic prompting is a reasoning technique inspired by the Socratic method where the model recursively generates explanations for its own statements, building a tree of logically…
doe
A main effect in DOE is the direct impact of changing a single factor on the response variable, averaged across all levels of the other factors. It answers the question: "What…
quality & reliability
Main Effect is the average response change attributable to one factor across levels of other factors - It is a core method in modern semiconductor statistical experimentation…
etch
The main etch is the primary phase of a plasma etch process responsible for bulk material removal — etching through the majority of the target film's thickness with the required…
production
The mainframe is the main body of a cluster tool housing the transfer chamber, vacuum system, and module interfaces, serving as the structural and functional core of the equipment…
manufacturing operations
Maintainability is the ease and speed with which equipment can be inspected, serviced, and restored to operation - It strongly affects downtime duration and maintenance labor…
code ai
Maintainability Index (MI) is a composite software metric that aggregates Halstead Volume, Cyclomatic Complexity, and Lines of Code into a single 0-100 score representing…
manufacturing operations
Maintenance Prevention is designing equipment and processes to eliminate recurrent maintenance burdens at the source - It shifts reliability improvement upstream into equipment…
maintenance technician response time prediction, maintenance technician response, technician response time, response time prediction, maintenance technician, response time
Maintenance Technician Response Time Prediction with Machine Learning Introduction & Motivation Maintenance Technician Response Time Prediction with Machine Learning addresses…
maintenance technician task duration prediction machine learning, maintenance technician, task duration prediction, cmms pm, maintenance technician task, technician task
Maintenance Technician Task Duration Prediction with Machine Learning Introduction & Motivation Maintenance Technician Task Duration Prediction with Machine Learning addresses…
production
Maintenance time tracking is the measurement of end-to-end maintenance cycle durations to identify where downtime is consumed and how repair response can be accelerated - it…
manufacturing operations
Maintenance Window is a planned time slot reserved for equipment maintenance activities with minimal production disruption - It is a core method in modern semiconductor operations…
maintenance work order backlog risk prediction, maintenance work order, work order backlog, order backlog risk, backlog risk prediction, maintenance work, work order
Maintenance Work Order Backlog Risk Prediction with Machine Learning Introduction & Motivation Maintenance Work Order Backlog Risk Prediction with Machine Learning addresses…
quality & reliability
Major Nonconformance is a severe breakdown indicating systemic failure or significant risk to product, compliance, or customer outcomes - It is a core method in modern…
majorana fermions and topological computing, majorana fermions topological, fermions topological computing, majorana fermions, fermions topological, topological computing
Majorana Fermions and Topological Computing Introduction & Motivation Majorana Fermions and Topological Computing addresses a central problem in quantum-hardware process control…
majorana zero mode operator clifford algebra anticommutation, kitaev 1d p wave superconductor Hamiltonian topological phase, non abelian anyon braiding fusion rules quantum gate
Majorana Zero Modes and Kitaev 1D Superconducting Wire: Non-Abelian Anyon Braiding in Topological Quantum Information 1. Introduction: Topological Quantum Computing and Majorana…
integromat, automate
Automation Strategy Overview Automation is the application of technology to produce and deliver goods and services with minimal human intervention. Moving from "Manual"…
make chip, how to make, build chip, create chip, fabricate chip, chip manufacturing, semiconductor fabrication, wafer processing, chip production
Making a modern chip means building a three-dimensional structure of 60–100+ patterned layers onto a silicon wafer, one atomic-scale layer at a time. At a high level, the flow…
multimodal ai
Make-A-Video is a text-to-video generation framework that adapts image generation priors to temporal synthesis - It demonstrates leveraging image models for efficient video…
automation, task
Makefiles are task automation files that serve as the executable documentation and command entry point for ML projects — replacing the problem of memorizing long, complex commands…
makeup air handler efficiency prediction machine learning, makeup air, handler efficiency prediction, mau, makeup air handler efficiency prediction, makeup air handler
Makeup Air Handler Efficiency Prediction with Machine Learning Introduction & Motivation Makeup Air Handler Efficiency Prediction with Machine Learning addresses a central problem…
malware detection signature storage and update, malware detection signature, detection signature storage, signature storage update, malware detection, detection signature
Malware Detection Signature Storage and Update Introduction & Motivation Malware Detection Signature Storage and Update addresses a central problem in security process control…
s4, state space model, ssm, linear attention, sequence model, alternative architecture
State space models (SSMs), and the Mamba architecture in particular, are a family of sequence models that challenge the Transformer's dominance by processing sequences in linear…
foundation model
State space models (SSMs), and the Mamba architecture in particular, are a family of sequence models that challenge the Transformer's dominance by processing sequences in linear…
mamba-2, mamba2, state space duality, ssd duality, structured state space duality, mamba 2 vs mamba, mamba two
Mamba-2 is the 2024 successor to the Mamba selective state-space model, and its importance is less about a bigger benchmark number than about a unifying idea: it shows that…
architecture
State space models (SSMs), and the Mamba architecture in particular, are a family of sequence models that challenge the Transformer's dominance by processing sequences in linear…
ssm sequence modeling, selective state spaces, structured state space s4, linear attention alternative
State space models (SSMs), and the Mamba architecture in particular, are a family of sequence models that challenge the Transformer's dominance by processing sequences in linear…
MAML Few-Shot Introduction & Motivation MAML Few-Shot addresses a central problem in fewshot and inner-loop-optimization architecture: how to Implement inner-loop-optimization…
gradient based meta learning, inner outer loop optimization, reptile meta learning, model agnostic meta
Meta-Learning (MAML) is the gradient-based optimization framework for learning to learn — computing meta-parameters (initialization) enabling rapid task-specific adaptation…
maml, model-agnostic meta-learning, few-shot learning
MAML (Model-Agnostic Meta-Learning) finds weight initialization enabling rapid adaptation to new tasks with gradient descent. Core idea: Learn θ such that few gradient steps on…
MAML Model-Agnostic Meta-Learning for Fast Adaptation Introduction & Motivation MAML Model-Agnostic Meta-Learning for Fast Adaptation addresses a central problem in fewshot…
meta reinforcement learning, few-shot rl
MAML for RL (Model-Agnostic Meta-Learning for Reinforcement Learning) applies the MAML meta-learning algorithm to enable RL agents to quickly adapt to new tasks with minimal…
maml-rl, reinforcement learning advanced
MAML-RL is model-agnostic meta-learning applied to reinforcement learning for fast gradient-based adaptation. - It finds parameter initializations that require only a few…
Mammalogy: Endothermy, Locomotion, Population Ecology, and Conservation Mammals range from tiny shrews to whales, occupy air, land, soil, freshwater, and ocean, and organize…
math, instruction
MAmmoTH is a mathematics-specialized language model created by fine-tuning Code Llama on diverse mathematical problem-solving data including step-by-step solutions, alternate…
mamo, recommendation systems
MAMO is memory-augmented meta-optimization for personalized recommendation adaptation. - It extends meta-learning with memory components that store reusable personalization…
Management Science: Strategy, Organizations, and Operational Decisions Management science studies how organizations set goals, allocate resources, coordinate work, learn…
l1, taxicab
Manhattan distance (also called L1 distance or taxicab distance) measures the distance between two points by summing absolute differences of coordinates, named after Manhattan's…
representation learning
Manifold Learning is the class of dimensionality reduction techniques that discover the intrinsic low-dimensional geometric structure (the manifold) embedded within…
data augmentation
Manifold Mixup is an extension of Mixup that performs interpolation in hidden layer representations rather than the input space — mixing intermediate features of the network…
Manifold Mixup for Invariant Boundary Interpolation Introduction & Motivation Manifold Mixup for Invariant Boundary Interpolation addresses a central problem in transfer learning…
Laplacian Support Vector Machines LapSVM Introduction & Motivation Laplacian Support Vector Machines LapSVM addresses a central problem in semisupervised…