Technology and the built world

Differential kinematics

Differential kinematics is the branch of robot kinematics describing how joint velocities map to the end effector's instantaneous linear and angular velocities, through the Jacobian matrix.

Differential pair

A differential pair is an amplifier stage in which two matched transistors share a single tail current and respond to the difference between their input voltages.

Oct 22, 2026

Differential phase-contrast scanning transmission electron microscopy

Differential phase-contrast scanning transmission electron microscopy (DPC STEM) is an electron microscopy technique that maps electric and magnetic fields inside a specimen by measuring how a focused electron probe is deflected.

Differential privacy

Differential privacy is a mathematical definition of privacy for data analysis, formalized in 2006, guaranteeing that results barely change whether or not any one person's data is included.

Differential privacy SGD

Differentially private stochastic gradient descent (DP-SGD) is a privacy-preserving variant of stochastic gradient descent, introduced by Abadi et al. in 2016 and the standard method for private neural network training.

Differential protection

Differential protection is a unit-protection technique in electrical power engineering that compares currents entering and leaving a zone, such as a transformer or busbar, and trips when the difference exceeds a threshold.

Differential pulse-code modulation

Differential pulse-code modulation (DPCM) is a signal coding method that transmits the difference between each sample and a prediction from past samples instead of the sample itself.

Differential quadrature phase-shift keying

Differential quadrature phase-shift keying (DQPSK) is a digital modulation scheme encoding two bits per symbol as phase shifts between successive symbols, requiring no reference carrier, used in optical fiber and cellular radio.

Differential signaling

Differential signaling is an electrical technique that carries information as the voltage difference between a pair of conductors, so noise appearing equally on both wires cancels.

Differential testing

Differential testing is a software testing method that feeds the same inputs to two or more comparable implementations, flagging any disagreement in their results as a possible bug.

Differentially private learning

Differentially private learning trains machine learning models while mathematically limiting how much any single individual's data can influence the model, by adding calibrated noise during optimization.

Differentially private stochastic gradient descent

Differentially private stochastic gradient descent (DP-SGD) is a training algorithm that clips each example's gradient and adds Gaussian noise, giving deep neural networks a formal differential privacy guarantee.

Differentiated services

Differentiated services, or Diffserv, is an IETF architecture for scalable quality of service in IP networks, standardized in December 1998 as RFC 2474 and RFC 2475.

Diffie–Hellman key exchange

Diffie–Hellman key exchange, also called key agreement, is a cryptographic protocol letting two parties establish a shared secret over a public channel, published in 1976.

Diffractive neural network

A diffractive neural network, or diffractive deep neural network, performs machine learning inference through light passing through trained diffractive layers, introduced by UCLA researchers in 2018.

Diffuser (compressor)

A diffuser in a compressor is a stationary passage downstream of the impeller that slows the working fluid, converting kinetic energy into static pressure, especially in centrifugal compressors.

Diffusion bonding

Diffusion bonding, also called diffusion welding, is a solid-state joining process in which heat and pressure unite clean surfaces by atomic diffusion without melting, used mainly in aerospace.

Diffusion brazing

Diffusion brazing, also known as transient liquid phase (TLP) bonding, is a joining process where a liquid filler diffuses into the base metal until the joint matches its strength.

Diffusion combustion

Diffusion combustion, also called non-premixed combustion, is combustion in which fuel and oxidizer start separate and burn where they mix, as in diesel engines and open fires.

Diffusion map

Diffusion map is a nonlinear dimensionality reduction method introduced by Ronald Coifman and Stéphane Lafon in 2006 that embeds high-dimensional data by running a random walk on a similarity graph.

Diffusion maps

Diffusion maps are a nonlinear manifold learning method introduced by Ronald Coifman and Stéphane Lafon in 2006, in which a random walk on the data yields eigenfunction coordinates describing its geometry.

Diffusion model

A diffusion model, also called a diffusion probabilistic model, is a generative neural network that produces data by learning to reverse a gradual noising process step by step.

Diffusion policies for robot control

A diffusion policy is a robot visuomotor control method that iteratively denoises random noise into chunks of future actions, introduced at Columbia University in March 2023.

Diffusion Policy

Diffusion Policy is a robot learning method representing a visuomotor policy as a conditional denoising diffusion process, introduced in March 2023 and improving manipulation performance by an average of 46.9%.

Diffusion samplers and solvers

Diffusion samplers and solvers are the numerical integration methods that turn a trained diffusion model's learned denoising directions into generated images or audio, deciding the speed–quality trade-off of every deployment.

Diffusion sampling (machine learning)

Diffusion sampling is the iterative procedure a diffusion model uses to turn random noise into images, audio, or other data, applying a denoising network repeatedly.

Diffusion transformer

A diffusion transformer (DiT) is a diffusion model whose denoising network is built from transformer blocks rather than a U-Net, established by William Peebles and Saining Xie in 2022.

Diffusion transformers (DiT)

A diffusion transformer (DiT) is a diffusion model using a Vision Transformer backbone, introduced by Peebles and Xie in 2022 and used in Sora and Stable Diffusion 3.

Diffusion welding

Diffusion welding is a solid-state joining process that bonds similar or dissimilar metals by heat and pressure, with atoms diffusing across the interface without melting.