Technology, Science and Universe
b
- Bilinear GAN Description: Bilinear Generative Adversarial Networks (GANs) are a variant of traditional GANs that incorporate bilinear operations into their(...) Read more
- Block Diagonal Matrix Description: A block diagonal matrix is a matrix structure composed of square submatrices arranged along its main diagonal, while all elements(...) Read more
- Boundary Loss Description: The 'Boundary Loss' is an innovative loss function specifically designed to enhance the boundary delineation between classes in(...) Read more
- Block-based Processing Description: Block-based processing is a technique used in convolutional neural networks (CNNs) that involves dividing images or data into(...) Read more
- Batch Validation Description: Batch validation is a crucial process in the field of machine learning, used to evaluate the performance of a trained model. This(...) Read more
- Binarized Activation Description: Binarized activation is an activation function that transforms the outputs of a neural network into binary values, typically 0 or(...) Read more
- Bi-directional LSTM Description: Bidirectional LSTMs (Long Short-Term Memory) are a type of recurrent neural network characterized by their ability to process data(...) Read more
- Binarized Weights Description: Binarized weights in convolutional neural networks are parameters that are limited to two possible values, typically -1 and +1,(...) Read more
- BPTT Description: BPTT, which stands for Backpropagation Through Time, is a fundamental technique for training recurrent neural networks (RNNs). This(...) Read more
- Bayesian RNN Description: Bayesian Recurrent Neural Networks (RNNs) are a type of recurrent neural network that combines the structure of recurrent neural(...) Read more
- Bilinear RNN Description: A bilinear RNN is a type of recurrent neural network that uses bilinear transformations to model interactions between inputs and(...) Read more
- BPTT Truncation Description: Truncation of BPTT (Backpropagation Through Time) is a technique used in recurrent neural networks (RNN) that limits the number of(...) Read more
- Block RNN Description: Block Recurrent Neural Networks (Block RNNs) are an advanced architecture of recurrent neural networks designed to process data in(...) Read more
- Boundary Condition Description: The 'Boundary Condition' in the context of Recurrent Neural Networks (RNNs) refers to the constraints applied to the input or(...) Read more
- Bilinear Form Description: The bilinear form is a mathematical function characterized by being linear in each of its two arguments separately. This means that(...) Read more
SPONSORS
