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STRUCTURED PREDICTION

  • Structured prediction
  • Supervised machine learning techniques

    predicting structured objects, rather than discrete or real values. Similar to commonly used supervised learning techniques, structured prediction models

    Structured prediction

    Structured_prediction

  • Protein structure prediction
  • Type of biological prediction

    Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its

    Protein structure prediction

    Protein structure prediction

    Protein_structure_prediction

  • Crystal structure prediction
  • Crystal structure prediction (CSP) is the calculation of the crystal structures of solids from first principles. Reliable methods of predicting the crystal

    Crystal structure prediction

    Crystal_structure_prediction

  • CASP
  • Protein structure prediction challenge

    Critical Assessment of Structure Prediction (CASP), sometimes called Critical Assessment of Protein Structure Prediction, is a community-wide, worldwide

    CASP

    CASP

    CASP

  • Secondary structure prediction
  • Topics referred to by the same term

    Secondary structure prediction is a set of techniques in bioinformatics that aim to predict the secondary structures of proteins and nucleic acid sequences

    Secondary structure prediction

    Secondary_structure_prediction

  • List of RNA structure prediction software
  • list of RNA structure prediction software is a compilation of software tools and web portals used for nucleic acid structure prediction. The single sequence

    List of RNA structure prediction software

    List_of_RNA_structure_prediction_software

  • List of protein structure prediction software
  • This list of protein structure prediction software summarizes notable used software tools in protein structure prediction, including homology modeling

    List of protein structure prediction software

    List of protein structure prediction software

    List_of_protein_structure_prediction_software

  • Large language model
  • Type of machine learning model

    that sequence into an embedding. On tasks such as structure prediction and mutational outcome prediction, a small model using an embedding as input can approach

    Large language model

    Large_language_model

  • Prediction
  • Statement about a future event

    prediction (from Latin prae- 'before' and dictum 'something said') or forecast is a statement about a future event or about future data. Predictions are

    Prediction

    Prediction

    Prediction

  • Recursive neural network
  • Type of neural network which utilizes recursion

    recursively over a structured input, to produce a structured prediction over variable-size input structures, or a scalar prediction on it, by traversing

    Recursive neural network

    Recursive_neural_network

  • Support vector machine
  • Set of methods for supervised statistical learning

    flexibility in being applied to a wide variety of tasks, including structured prediction problems. It is not clear that SVMs have better predictive performance

    Support vector machine

    Support_vector_machine

  • AlphaFold
  • Artificial intelligence program by DeepMind

    developed by DeepMind, a subsidiary of Alphabet, which performs predictions of protein structure. It is designed using deep learning techniques. AlphaFold 1

    AlphaFold

    AlphaFold

    AlphaFold

  • Mamba (deep learning architecture)
  • Deep learning architecture

    is based on the Structured State Space sequence (S4) model. To enable handling long data sequences, Mamba incorporates the Structured State Space sequence

    Mamba (deep learning architecture)

    Mamba_(deep_learning_architecture)

  • Kernel method
  • Class of algorithms for pattern analysis

    y_{i})} and learn for it a corresponding weight w i {\displaystyle w_{i}} . Prediction for unlabeled inputs, i.e., those not in the training set, are treated

    Kernel method

    Kernel_method

  • Machine learning
  • Subset of artificial intelligence

    output distribution). Conversely, an optimal compressor can be used for prediction (by finding the symbol that compresses best, given the previous history)

    Machine learning

    Machine_learning

  • Diffusion model
  • Technique for the generative modeling of a continuous probability distribution

    }(x_{t},t)-z\right\|^{2}\right]} resulted in better models. After a noise prediction network is trained, it can be used for generating data points in the original

    Diffusion model

    Diffusion_model

  • Automated machine learning
  • Process of automating the application of machine learning

    such as data engineering, data exploration and model interpretation and prediction. Automated machine learning can target various stages of the machine learning

    Automated machine learning

    Automated_machine_learning

  • Feature scaling
  • Method used to normalize the range of independent variables

    (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer. ISBN 978-0-387-84884-6. Han, Jiawei; Kamber, Micheline; Pei

    Feature scaling

    Feature_scaling

  • Conditional random field
  • Class of statistical modeling methods

    applied in pattern recognition and machine learning and used for structured prediction. Whereas a classifier predicts a label for a single sample without

    Conditional random field

    Conditional_random_field

  • Transfer learning
  • Machine learning technique

    (2017-11-08). DA-HOC: semi-supervised domain adaptation for room occupancy prediction using CO2 sensor data. 4th ACM International Conference on Systems for

    Transfer learning

    Transfer learning

    Transfer_learning

  • U-Net
  • Type of convolutional neural network

    translation to estimate fluorescent stains In binding site prediction of protein structure. U-Net was created by Olaf Ronneberger, Philipp Fischer, Thomas

    U-Net

    U-Net

  • Platt scaling
  • Machine learning calibration technique

    large networks like ResNet has high accuracy but is overconfident in predictions. A 2017 paper proposed temperature scaling, which simply multiplies the

    Platt scaling

    Platt_scaling

  • Outline of machine learning
  • Overview of and topical guide to machine learning

    Reinforcement Learning Semi-supervised learning Statistical learning Structured prediction Graphical models Bayesian network Conditional random field (CRF)

    Outline of machine learning

    Outline_of_machine_learning

  • John M. Jumper
  • American chemist and computer scientist (born 1985)

    Baker were awarded the 2024 Nobel Prize in Chemistry for protein structure prediction. Jumper served as a director at Google DeepMind for nearly nine years

    John M. Jumper

    John M. Jumper

    John_M._Jumper

  • Transformer (deep learning)
  • Algorithm for modelling sequential data

    pretraining and fine-tuning commonly include: language modeling next-sentence prediction question answering reading comprehension sentiment analysis paraphrasing

    Transformer (deep learning)

    Transformer (deep learning)

    Transformer_(deep_learning)

  • Neuromorphic computing
  • Integrated circuit technology

    Neuromorphic computing is a computing approach inspired by the human brain's structure and function. It uses artificial neurons to perform computations, mimicking

    Neuromorphic computing

    Neuromorphic_computing

  • Active learning (machine learning)
  • Machine learning strategy

    individual data instances. The candidate instances are those for which the prediction is most ambiguous. Instances are drawn from the entire data pool and assigned

    Active learning (machine learning)

    Active_learning_(machine_learning)

  • Structured support vector machine
  • Machine learning algorithm

    multiclass classification and regression, the structured SVM allows training of a classifier for general structured output labels. As an example, a sample instance

    Structured support vector machine

    Structured_support_vector_machine

  • Attention (machine learning)
  • Machine learning technique

    arXiv:2010.11929. Jumper, John (2021). "Highly accurate protein structure prediction with AlphaFold". Nature. 596 (7873): 583–589. Bibcode:2021Natur.596

    Attention (machine learning)

    Attention (machine learning)

    Attention_(machine_learning)

  • Regression analysis
  • Set of statistical processes for estimating the relationships among variables

    conceptually distinct purposes. First, regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field

    Regression analysis

    Regression analysis

    Regression_analysis

  • Gated recurrent unit
  • Memory unit used in neural networks

    Jürgen Schmidhuber; Fred Cummins (1999). "Learning to forget: Continual prediction with LSTM". 9th International Conference on Artificial Neural Networks:

    Gated recurrent unit

    Gated_recurrent_unit

  • Leakage (machine learning)
  • Concept in machine learning

    use of information during model training that would not be available at prediction time. This results in overly optimistic performance estimates, as the

    Leakage (machine learning)

    Leakage_(machine_learning)

  • Feature (machine learning)
  • Measurable property or characteristic

    linear predictor function that is used to determine a score for making a prediction. The vector space associated with these vectors is often called the feature

    Feature (machine learning)

    Feature_(machine_learning)

  • Link prediction
  • Problem in network theory

    independently. Structured prediction approaches capture the correlation between potential links by formulating the task as a collective link prediction task. Collective

    Link prediction

    Link_prediction

  • Nucleic acid structure prediction
  • Computational prediction of nucleic acid structure

    acid structure prediction is a computational method to determine secondary and tertiary nucleic acid structure from its sequence. Secondary structure can

    Nucleic acid structure prediction

    Nucleic_acid_structure_prediction

  • Multimodal learning
  • Machine learning methods using multiple input modalities

    generation, all input tokens are masked, and the highest-confidence predictions are included for the next iteration, until all tokens are predicted.

    Multimodal learning

    Multimodal_learning

  • Random forest
  • Tree-based ensemble machine learning methods

    by most trees. For regression tasks, the output is the average of the predictions of the trees. Random forests correct for decision trees' habit of overfitting

    Random forest

    Random_forest

  • De novo protein structure prediction
  • Predicting 3D protein structure from its sequence

    computational biology, de novo protein structure prediction refers to an algorithmic process by which protein tertiary structure is predicted from its amino acid

    De novo protein structure prediction

    De_novo_protein_structure_prediction

  • David Baker (biochemist)
  • American biochemist and computational biologist (born 1962)

    develop biomolecular structure prediction and design software. His group has regularly competed in the CASP structure prediction competition, specializing

    David Baker (biochemist)

    David Baker (biochemist)

    David_Baker_(biochemist)

  • Statistical learning theory
  • Framework for machine learning

    recognition, and bioinformatics. The goals of learning are understanding and prediction. Learning falls into many categories, including supervised learning, unsupervised

    Statistical learning theory

    Statistical_learning_theory

  • Feedforward neural network
  • Type of artificial neural network

    also known as linear regression. Legendre and Gauss used it for the prediction of planetary movement from training data. In 1943, Warren McCulloch and

    Feedforward neural network

    Feedforward neural network

    Feedforward_neural_network

  • Reinforcement learning
  • Field of machine learning

    similarly to dynamic programming to achieve optimality, first addressing the prediction problem and then extending to policy improvement and control, all based

    Reinforcement learning

    Reinforcement learning

    Reinforcement_learning

  • Word2vec
  • Models used to produce word embeddings

    used in similar contexts. The order of context words does not influence prediction (bag of words assumption). In the continuous skip-gram architecture, the

    Word2vec

    Word2vec

  • Prediction market
  • Platforms for betting on events

    Prediction markets, also known as betting markets, information markets, decision markets, idea futures, or event derivatives, are open markets that enable

    Prediction market

    Prediction_market

  • Softmax function
  • Smooth approximation of one-hot arg max

    probability predictions densely distributed over its support. Other functions like sparsemax or α-entmax can be used when sparse probability predictions are desired

    Softmax function

    Softmax_function

  • Recurrent neural network
  • Class of artificial neural network

    of proteins Several prediction tasks in the area of business process management Prediction in medical care pathways Predictions of fusion plasma disruptions

    Recurrent neural network

    Recurrent_neural_network

  • Neural architecture search
  • Machine learning-powered structure design

    consumption, model size or inference time (i.e., the time required to obtain a prediction). Because of that, researchers created a multi-objective search. LEMONADE

    Neural architecture search

    Neural_architecture_search

  • Feature engineering
  • Extracting features from raw data for machine learning

    purpose of being used to either train models (by data scientists) or make predictions (by applications that have a trained model). It is a central location

    Feature engineering

    Feature_engineering

  • Backpropagation
  • Optimization algorithm for artificial neural networks

    Prediction by Using a Connectionist Network with Internal Delay Lines". In Weigend, Andreas S.; Gershenfeld, Neil A. (eds.). Time Series Prediction:

    Backpropagation

    Backpropagation

  • Protein secondary structure
  • General three-dimensional form of local segments of proteins

    to PDB structures, against which the predictions are benchmarked. Accurate secondary-structure prediction is a key element in the prediction of tertiary

    Protein secondary structure

    Protein secondary structure

    Protein_secondary_structure

  • Temporal difference learning
  • Computer programming concept

    estimates once the outcome is known, TD methods adjust predictions to match later, more-accurate predictions about the future, before the outcome is known. This

    Temporal difference learning

    Temporal_difference_learning

  • Long short-term memory
  • Recurrent neural network architecture

    the LSTM network to maintain useful, long-term dependencies to make predictions, both in current and future time-steps. LSTM has wide applications in

    Long short-term memory

    Long short-term memory

    Long_short-term_memory

  • Self-supervised learning
  • Machine learning paradigm

    generated labels that a model assigns to unlabeled data based on its own predictions. They are widely used in self-supervised and semi-supervised learning

    Self-supervised learning

    Self-supervised_learning

  • Differentiable programming
  • Programming paradigm

    biophysics-based modelling of molecular mechanisms, in areas such as protein structure prediction and drug discovery. These applications demonstrate the potential

    Differentiable programming

    Differentiable_programming

  • Variational autoencoder
  • Deep learning generative model to encode data representation

    ML]. Sohn, Kihyuk; Lee, Honglak; Yan, Xinchen (2015-01-01). Learning Structured Output Representation using Deep Conditional Generative Models (PDF).

    Variational autoencoder

    Variational autoencoder

    Variational_autoencoder

  • Empirical risk minimization
  • Principle in statistical learning theory

    y ) {\displaystyle L({\hat {y}},y)} which measures how different the prediction y ^ {\displaystyle {\hat {y}}} of a hypothesis is from the true outcome

    Empirical risk minimization

    Empirical_risk_minimization

  • Graph neural network
  • Class of artificial neural networks

    the corresponding node representations in the same way. For graph-level prediction tasks, GNNs typically use a permutation-invariant readout function, whose

    Graph neural network

    Graph_neural_network

  • Data augmentation
  • Data analysis technique

    classification performance was improved when such techniques were introduced. The prediction of mechanical signals based on data augmentation brings a new generation

    Data augmentation

    Data_augmentation

  • GPT-2
  • 2019 text-generating language model

    performing a single prediction "can occupy a CPU at 100% utilization for several minutes", and even with GPU processing, "a single prediction can take seconds"

    GPT-2

    GPT-2

    GPT-2

  • Neural network (machine learning)
  • Computational model used in machine learning

    onward, the use of neural networks transformed the field of protein structure prediction, in particular when the first cascading networks were trained on

    Neural network (machine learning)

    Neural network (machine learning)

    Neural_network_(machine_learning)

  • Protein
  • Biomolecule consisting of chains of amino acid residues

    protein. Linus Pauling is credited with the successful prediction of regular protein secondary structures based on hydrogen bonding, an idea first put forth

    Protein

    Protein

    Protein

  • Decision tree learning
  • Machine learning algorithm

    training data with replacement, and voting the trees for a consensus prediction. A random forest classifier is a specific type of bootstrap aggregating

    Decision tree learning

    Decision_tree_learning

  • Ensemble learning
  • Statistics and machine learning technique

    a hypothesis space to find a suitable hypothesis that will make good predictions with a particular problem. Even if this space contains hypotheses that

    Ensemble learning

    Ensemble_learning

  • Rosetta@home
  • BOINC based volunteer computing project researching protein folding

    Rosetta@home is a volunteer computing project researching protein structure prediction on the Berkeley Open Infrastructure for Network Computing (BOINC)

    Rosetta@home

    Rosetta@home

    Rosetta@home

  • Training, validation, and test data sets
  • Tasks in machine learning

    algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical

    Training, validation, and test data sets

    Training,_validation,_and_test_data_sets

  • Perceptron
  • Algorithm for supervised learning of binary classifiers

    of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with

    Perceptron

    Perceptron

  • Pattern recognition
  • Automated recognition of patterns and regularities in data

    Weiss, Sholom M. (1991). Computer Systems That Learn: Classification and Prediction Methods from Statistics, Neural Nets, Machine Learning, and Expert Systems

    Pattern recognition

    Pattern_recognition

  • Convolutional neural network
  • Type of feedforward neural network

    This type of deep learning network has been applied to process and make predictions from many different types of data including text, images and audio. CNNs

    Convolutional neural network

    Convolutional_neural_network

  • Overfitting
  • Flaw in mathematical modelling

    see Figure 2.) Such a model will typically fail severely when making predictions. Overfitting is related to both the complexity of the chosen model and

    Overfitting

    Overfitting

    Overfitting

  • Rule-based machine learning
  • AI that learns decision rules from data

    comprise a set of rules, or knowledge base, that collectively make up the prediction model usually known as decision algorithm. Rules can also be interpreted

    Rule-based machine learning

    Rule-based_machine_learning

  • Hierarchical clustering
  • Statistical method in data analysis

    deliberately restricted to manageable downscaled subsamples, while label prediction can be applied broadly to the full dataset once the hierarchy and classifiers

    Hierarchical clustering

    Hierarchical_clustering

  • Demis Hassabis
  • British AI researcher (born 1976)

    Prize in Chemistry for their AI research contributions to protein structure prediction. Hassabis is a Fellow of the Royal Society and has won awards for

    Demis Hassabis

    Demis Hassabis

    Demis_Hassabis

  • Meta-learning (computer science)
  • Subfield of machine learning

    learning problem, the predictions of the selected set of algorithms are combined (e.g. by (weighted) voting) to provide the final prediction. Since each algorithm

    Meta-learning (computer science)

    Meta-learning_(computer_science)

  • Vision transformer
  • Machine learning model for vision processing

    have found application in image recognition, image segmentation, weather prediction, and autonomous driving. Transformers were introduced in Attention Is

    Vision transformer

    Vision transformer

    Vision_transformer

  • Bias–variance tradeoff
  • Property of a model

    between a model's complexity, the accuracy of its predictions, and how well it can make predictions on previously unseen data that were not used to train

    Bias–variance tradeoff

    Bias–variance tradeoff

    Bias–variance_tradeoff

  • Data mining
  • Process of analyzing large data sets

    multiple groups in the data, which can then be used to obtain more accurate prediction results by a decision support system. Neither the data collection, data

    Data mining

    Data_mining

  • Imitation learning
  • Machine learning technique where agents learn from demonstrations

    Bagnell, Drew (2011-06-14). "A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning". Proceedings of the Fourteenth International

    Imitation learning

    Imitation_learning

  • Gradient boosting
  • Machine learning technique

    residuals as in traditional boosting. It gives a prediction model in the form of an ensemble of weak prediction models, i.e., models that make very few assumptions

    Gradient boosting

    Gradient_boosting

  • Protein tertiary structure
  • Three dimensional shape of a protein

    geometry into the prediction of protein structures. Wrinch demonstrated this with the Cyclol model, the first prediction of the structure of a globular protein

    Protein tertiary structure

    Protein tertiary structure

    Protein_tertiary_structure

  • Sentence embedding
  • Representation in natural language processing

    sentences. Skip-Thought trains an encoder-decoder structure for the task of neighboring sentences predictions; this has been shown to achieve worse performance

    Sentence embedding

    Sentence_embedding

  • Biomolecular structure
  • 3D conformation of a biological sequence, like DNA, RNA, proteins

    secondary structure of RNA molecules. Approaches include both experimental and computational methods (see also the List of RNA structure prediction software)

    Biomolecular structure

    Biomolecular structure

    Biomolecular_structure

  • AdaBoost
  • Adaptive boosting based classification algorithm

    learner produces an output hypothesis h {\displaystyle h} which fixes a prediction h ( x i ) {\displaystyle h(x_{i})} for each sample in the training set

    AdaBoost

    AdaBoost

  • Graphical model
  • Probabilistic model

    model (PGM) or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random

    Graphical model

    Graphical_model

  • Protein structure
  • Three-dimensional arrangement of atoms in an amino acid-chain molecule

    methods for the computational prediction of protein structure from its sequence have been developed. Ab initio prediction methods use just the sequence

    Protein structure

    Protein structure

    Protein_structure

  • Learning to rank
  • Use of machine learning to rank items

    translations; In computational biology for ranking candidate 3-D structures in protein structure prediction problems; In recommender systems for identifying a ranked

    Learning to rank

    Learning_to_rank

  • Anomaly detection
  • Approach in data analysis

    compute the mean or standard deviation. They were also removed to better predictions from models such as linear regression, and more recently their removal

    Anomaly detection

    Anomaly_detection

  • Levinthal's paradox
  • Thought experiment of protein folding

    paradox is a thought experiment in the field of computational protein structure prediction that concerns the mechanism through which peptides reach a stable

    Levinthal's paradox

    Levinthal's_paradox

  • Topological deep learning
  • Research field in deep learning

    often operate under the assumption that a dataset is residing in a highly-structured space (like images, where convolutional neural networks exhibit outstanding

    Topological deep learning

    Topological_deep_learning

  • List of protein subcellular localization prediction tools
  • these tools output predictions of these features rather than specific locations. These software related to protein structure prediction may also appear in

    List of protein subcellular localization prediction tools

    List_of_protein_subcellular_localization_prediction_tools

  • Constrained conditional model
  • Machine learning and inference framework

    the correct (or optimal) learning representation is viewed as a structured prediction process and therefore modeled as a CCM. This problem was covered

    Constrained conditional model

    Constrained_conditional_model

  • Autoencoder
  • Neural network that learns efficient data encoding in an unsupervised manner

    (2014). "Deep autoencoder neural networks for gene ontology annotation predictions". Proceedings of the 5th ACM Conference on Bioinformatics, Computational

    Autoencoder

    Autoencoder

    Autoencoder

  • Lists of engineering software
  • Lists of software used in various branches of engineering

    list of open-source libraries List of protein structure prediction software List of RNA structure prediction software List of robotics software List of scientific

    Lists of engineering software

    Lists_of_engineering_software

  • Computational learning theory
  • Theory of machine learning

    Computational Learning Theory, (1988) 42-55. Pitt, L.; Warmuth, M. K. (1990). "Prediction-Preserving Reducibility". Journal of Computer and System Sciences. 41

    Computational learning theory

    Computational_learning_theory

  • Random sample consensus
  • Statistical method

    the fundamental matrix related to a pair of stereo cameras; see also: Structure from motion, scale-invariant feature transform, image stitching, rigid

    Random sample consensus

    Random_sample_consensus

  • Sequence analysis
  • Identification and study of genomic sequences

    were most effective, a structure prediction competition was founded called CASP (Critical Assessment of Structure Prediction). Sequence analysis tasks

    Sequence analysis

    Sequence_analysis

  • List of disorder prediction software
  • been recently updated, shows the main features of software for disorder prediction. Note that different software use different definitions of disorder. Methods

    List of disorder prediction software

    List_of_disorder_prediction_software

  • Deep belief network
  • Type of artificial neural network

    "The Role of Different Sampling Methods in Improving Biological Activity Prediction Using Deep Belief Network". Journal of Computational Chemistry. 38 (10):

    Deep belief network

    Deep belief network

    Deep_belief_network

  • Incremental learning
  • Method of machine learning

    in data availability and resource scarcity respectively. Stock trend prediction and user profiling are some examples of data streams where new data becomes

    Incremental learning

    Incremental_learning

  • Earthquake prediction
  • Branch of geophysics, primarily seismology

    Earthquake prediction is an operational objective within the broader framework of earthquake forecasting, specifically representing a forecast where uncertainty

    Earthquake prediction

    Earthquake_prediction

  • List of gene prediction software
  • software tools and web portals used for gene prediction. Gene prediction List of RNA structure prediction software Comparison of software for molecular

    List of gene prediction software

    List_of_gene_prediction_software

AI & ChatGPT searchs for online references containing STRUCTURED PREDICTION

STRUCTURED PREDICTION

AI search references containing STRUCTURED PREDICTION

STRUCTURED PREDICTION

  • Casandra
  • Girl/Female

    Spanish American

    Casandra

    Unheeded prophetess. In Homer's 'The Iliad' Cassandra's prediction of the fall of Troy was unheeded.

    Casandra

  • Aakruti
  • Girl/Female

    Indian

    Aakruti

    Shape, Structure

    Aakruti

  • Rupeksha
  • Girl/Female

    Hindu, Indian, Telugu

    Rupeksha

    The Structure of God

    Rupeksha

  • Arica
  • Girl/Female

    German, Nigerian

    Arica

    Prediction of the Winds; Ever Powerful Ruler

    Arica

  • Kayya
  • Girl/Female

    Indian

    Kayya

    Structure

    Kayya

  • Aakruti | ஆகரதி
  • Girl/Female

    Tamil

    Aakruti | ஆகரதி

    Shape, Structure

    Aakruti | ஆகரதி

  • Omran
  • Boy/Male

    Indian

    Omran

    Solid structure

    Omran

  • Aakruthi
  • Girl/Female

    Indian

    Aakruthi

    Shape, Structure

    Aakruthi

  • Rishal
  • Boy/Male

    Indian

    Rishal

    Good Structure

    Rishal

  • Kassie
  • Girl/Female

    English American

    Kassie

    Abbreviation of Cassandra. Unheeded prophetess. In Homer's 'The Iliad' Cassandra's prediction of...

    Kassie

  • Kayaa
  • Girl/Female

    Indian, Kashmiri

    Kayaa

    Body Structure

    Kayaa

  • Omran | اومران
  • Boy/Male

    Muslim

    Omran | اومران

    Solid structure

    Omran | اومران

  • Omran
  • Boy/Male

    Afghan, Arabic, Gujarati, Indian, Muslim

    Omran

    Solid Structure; Lifetime

    Omran

  • Cassy
  • Girl/Female

    English

    Cassy

    Abbreviation of Cassandra. Unheeded prophetess. In Homer's 'The Iliad' Cassandra's prediction of...

    Cassy

  • Cassi
  • Girl/Female

    English

    Cassi

    Abbreviation of Cassandra. Unheeded prophetess. In Homer's 'The Iliad' Cassandra's prediction of...

    Cassi

  • Aakruthi | ஆகரதீ
  • Girl/Female

    Tamil

    Aakruthi | ஆகரதீ

    Shape, Structure

    Aakruthi | ஆகரதீ

  • URIEL
  • Male

    English

    URIEL

    (אוּרִיאֵל) Anglicized form of Hebrew Uwriyel, URIEL means "flame of God" or "light of the Lord." In the bible, this is the name of a Levite, and the maternal grandfather of Abijah. It is also the name of one of the seven archangels whose names were removed from the Church's list of recognized angels in 145 A.D. He was said to have been one of the angels stationed at God's throne. He was considered the wisest of the archangels because his light was not merely of the physical kind, but rather the ultra-spiritual kind, making him highly intellectually illuminated. Some think Uriel was the angel who warned Noah of the coming flood, and helped the prophet Ezra interpret a prediction concerning the coming Messiah. He is also said to be the angel of divine magic, alchemy, writing, earthquakes, floods, and other kinds of cataclysms. 

    URIEL

  • Kassandra
  • Girl/Female

    Greek American

    Kassandra

    Unheeded prophetess. In Homer's 'The Iliad' Cassandra's prediction of the fall of Troy was unheeded.

    Kassandra

  • Watler
  • Surname or Lastname

    English

    Watler

    English : occupational name for a wattler, Middle English watelere, i.e. someone who made the panels of interwoven twigs that were used to fill the spaces between the structural timbers of a timber frame building. See also Dauber.

    Watler

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Online names & meanings

  • Bassim
  • Boy/Male

    Arabic, Australian, Muslim

    Bassim

    Smiling

  • Chaitnik
  • Boy/Male

    Hindu, Indian

    Chaitnik

    Aiways Peaceful Mind

  • Bryngerd
  • Girl/Female

    Norse

    Bryngerd

    Mother of Tongue-Stein.

  • Sivaram
  • Boy/Male

    Indian, Tamil, Telugu

    Sivaram

    Lord Siva; Lord Hari

  • Deanda
  • Girl/Female

    English

    Deanda

    Blend of Deanne: (divine) plus variants of Andrea: (masculine) and Sandra: (protector of man. ).

  • Chinmayee
  • Boy/Male

    Hindu

    Chinmayee

  • Berriman
  • Surname or Lastname

    English

    Berriman

    English : variant spelling of Berryman.

  • Borrowman
  • Surname or Lastname

    English

    Borrowman

    English : status name from Middle English burghman, borughman (Old English burhmann) ‘inhabitant of a (fortified) town’ (see Burke), especially one holding land or buildings by burgage (see Burgess).

  • BENEDETTO
  • Male

    Italian

    BENEDETTO

    Italian form of Latin Benedictus, BENEDETTO means "blessed." 

  • Zedekiah
  • Boy/Male

    Hebrew Biblical

    Zedekiah

    The Lord is righteous; God's justice.

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STRUCTURED PREDICTION

  • Stricture
  • n.

    A stroke; a glance; a touch.

  • Structure
  • n.

    Arrangement of parts, of organs, or of constituent particles, in a substance or body; as, the structure of a rock or a mineral; the structure of a sentence.

  • Stricture
  • n.

    A touch of adverse criticism; censure.

  • Structure
  • n.

    The act of building; the practice of erecting buildings; construction.

  • Structural
  • a.

    Of or pertaining to organit structure; as, a structural element or cell; the structural peculiarities of an animal or a plant.

  • Shaly
  • a.

    Resembling shale in structure.

  • Organism
  • n.

    Organic structure; organization.

  • Structural
  • a.

    Of or pertaining to structure; affecting structure; as, a structural error.

  • Stricture
  • n.

    A localized morbid contraction of any passage of the body. Cf. Organic stricture, and Spasmodic stricture, under Organic, and Spasmodic.

  • Compagination
  • n.

    Union of parts; structure.

  • Dentigerous
  • a.

    Bearing teeth or toothlike structures.

  • Making
  • n.

    Composition, or structure.

  • Strictured
  • a.

    Affected with a stricture; as, a strictured duct.

  • Structure
  • n.

    Manner of organization; the arrangement of the different tissues or parts of animal and vegetable organisms; as, organic structure, or the structure of animals and plants; cellular structure.

  • High-built
  • a.

    Of lofty structure; tall.

  • Structure
  • n.

    That which is built; a building; esp., a building of some size or magnificence; an edifice.

  • Structure
  • n.

    Manner of building; form; make; construction.

  • Fabric
  • n.

    Framework; structure; edifice; building.

  • Structured
  • a.

    Having a definite organic structure; showing differentiation of parts.

  • Stricture
  • n.

    Strictness.