A temporal network, also known as a time-varying network, is a network whose links are active only at certain points in time. Each link carries information...

spatial networks have been developed. Other networks emphasise the evolution over time of systems of nodes and their interconnections. Temporal networks are...

behavior of networks into account. DNA is tied to temporal analysis but temporal analysis is not necessarily tied to DNA, as changes in networks sometimes...

the temporal behavior of other unrelated processes running on the same system, thus sharing with it a set of resources such as the CPU, disk, network, etc...

biological neural network within a single cerebral hemisphere. Temporal lobe epilepsy occurs from seizures arising within the temporal lobe. Temporal lobe epilepsy...

Spatial–temporal reasoning is an area of artificial intelligence that draws from the fields of computer science, cognitive science, and cognitive psychology...

The Simple Temporal Network with Uncertainty (STNU) is a scheduling problem which involves controllable actions, uncertain events and temporal constraints...

Connectionist temporal classification (CTC) is a type of neural network output and associated scoring function, for training recurrent neural networks (RNNs)...

convolutional neural networks perform video super-resolution by storing temporal dependencies. STCN (the spatio-temporal convolutional network) extract features...

Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive...

Hierarchical temporal memory (HTM) is a biologically constrained machine intelligence technology developed by Numenta. Originally described in the 2004...

transmission Poisson clumping Time-varying network Lambiotte, R. (2013.) "Burstiness and Spreading on Temporal Networks", University of Namur. Neuts, M. F. (1993...

between the prehistoric and the other samples, placing them in the temporal network between the Eneolithic Age and the Roman Age. A couple of mitochondrial...

Temporal difference (TD) learning refers to a class of model-free reinforcement learning methods which learn by bootstrapping from the current estimate...

powerful tools such as Convolutional Neural Networks (CNNs). However, effective methods for incorporation of temporal information into CNNs are still being...

and temporal attention, the most critical spatial regions/temporal instants could be visualized to justify the CNN predictions. A deep Q-network (DQN)...

difference was also reflected in the differential activation of the fronto-temporal network, higher activation for non self-serving attributions in non-depressed...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure...

Temporal Key Integrity Protocol (TKIP /tiːˈkɪp/) is a security protocol used in the IEEE 802.11 wireless networking standard. TKIP was designed by the...

personal network Supply network, a pattern of temporal and spatial processes carried out at facility nodes and over distribution links Transport network, a...

e., raining cats and dogs), the Broca’s area in the left prefronto-temporal network was activated. However, when literally interpretable idioms (i.e.,...

Middle temporal gyrus is a gyrus in the brain on the temporal lobe. It is located between the superior temporal gyrus and inferior temporal gyrus. It corresponds...

clustering with spiking neurons by sparse temporal coding and multilayer RBF networks". IEEE Transactions on Neural Networks. 13 (2): 426–435. doi:10.1109/72.991428...

the time varying input into a spatio-temporal pattern of activations in the network nodes. The spatio-temporal patterns of activation are read out by...

systems, including techniques of dynamic network analysis. Mechanisms such as Dual-phase evolution explain how temporal changes in connectivity contribute to...

Conversely, the Markov network responsible for detection builds the object proposal graph with inputs including the spatio-temporal segmentation tubes. Graph...

method. DLAA uses an auto-encoder convolutional neural network trained to identify and fix temporal artifacts, instead of manually programmed heuristics...

specific context of a dynamic Bayesian network, the conditional distribution for the hidden state's temporal evolution is commonly specified to maximize...

records. The climate network approach enables novel insights into the dynamics of the climate system over different spatial and temporal scales. Depending...

one time step is fed back as input to the network at the next time step. This enables RNNs to capture temporal dependencies and patterns within sequences...