Technology, Science and Universe
b
- Bayesian classifier Description: A Bayesian classifier is a statistical classifier that applies Bayes' theorem with strong independence assumptions (naive). This(...) Read more
- Binary Cross-Entropy Description: Binary cross-entropy is a loss function widely used in the field of machine learning, especially in binary classification tasks.(...) Read more
- Bayesian Network Classifier Description: A Bayesian network classifier is a probabilistic model that uses a Bayesian network to classify data. This type of classifier is(...) Read more
- Binary Decision Tree Description: A binary decision tree is a decision support tool that uses a tree-like graph of decisions and their possible consequences. This(...) Read more
- Block-based Learning Description: Block-based learning refers to a learning paradigm where data is processed in blocks rather than as a whole. This approach allows(...) Read more
- Bayesian Model Averaging Description: Bayesian model averaging is a statistical approach that integrates the inherent uncertainty of models by averaging over multiple(...) Read more
- Bottleneck Layer Description: The bottleneck layer is a crucial component in neural network architectures, particularly in various types such as recurrent neural(...) Read more
- Bidirectional LSTM Description: Bidirectional LSTM (Long Short-Term Memory) is an advanced type of recurrent neural network (RNN) used for processing sequences of(...) Read more
- Binarized Neural Network Description: A binarized neural network is a type of neural network where weights and, in some cases, activations are restricted to binary(...) Read more
- Bayesian Neural Network Description: A Bayesian neural network is a type of neural network that incorporates Bayesian inference to estimate uncertainty in its(...) Read more
- Bilinear Pooling Description: Bilinear pooling is a method in the field of Deep Learning that allows for the combination of features from two different sources,(...) Read more
- Bottom-Up Attention Description: Bottom-up attention is an attention mechanism in the field of deep learning that focuses on identifying and highlighting salient(...) Read more
- Batch Sampling Description: Batch sampling is a method of selecting a subset of data points from a larger dataset in batches. This approach is fundamental in(...) Read more
- Bottleneck Architecture Description: Bottleneck architecture in neural networks refers to a design that includes specific layers that limit the amount of information(...) Read more
- Block-wise Training Description: Block training is a training method in the field of Deep Learning that focuses on processing data in segments or blocks, rather(...) Read more
SPONSORS
