Building Blocks for Biofabricated Models

Building Blocks for Hierarchical Latent Variable Models

We introduce building blocks from which a large variety of latent variable models can be built. The blocks include continuous and discrete variables, summation, addition, nonlinearity and switching. Ensemble learning provides a cost function which can be used for updating the variables as well as optimising the model structure. The blocks are designed to fit together and to yield efficient upda...

Building Blocks for Variational Bayesian Learning of Latent Variable Models

We introduce standardised building blocks designed to be used with variational Bayesian learning. The blocks include Gaussian variables, summation, multiplication, nonlinearity, and delay. A large variety of latent variable models can be constructed from these blocks, including nonlinear and variance models, which are lacking from most existing variational systems. The introduced blocks are des...

Building Blocks for Nanotransporters

Evaluation of Updating Methods in Building Blocks Dataset

With the increasing use of spatial data in daily life, the production of this data from diverse information sources with different precision and scales has grown widely. Generating new data requires a great deal of time and money. Therefore, one solution is to reduce costs is to update the old data at different scales using new data (produced on a similar scale). One approach to updating data i...

Building Blocks for Agent Design

We present our Component-Based Agent Framework, which enables a software engineer to design a set of agents by using a visual compo nent-based toolkit (Sun’s BDK), and wiring together desired blocks of functionality. We instantiate this framework in the RoboCup domain by implementing the necessary components. The implementation also serves as a proof of the viability of our framework. Finally, ...