Abstract: The present invention relates to a computer implemented method (30) for transforming a pre-trained neural network.

Abstract: A deep approximation neural network architecture which extrapolates data over unseen states for demand response applications in order to control distribution systems like product distribution systems of which energy distribution systems, e.g. heat or electrical power distribution, are one example. The method is a model-free control technique mainly in the form of Reinforcement Learning (RL) where a controller learns from interaction with the system to be controlled to control product distributions of which energy distribution systems, e.g. heat or electrical power distribution, are one example.

Abstract: There is described a machine learning system comprising a first subsystem and a second subsystem remote from the first subsystem. The first subsystem comprises an environment having multiple possible states and a decision making subsystem comprising one or more agents. Each agent is arranged to receive state information indicative of a current state of the environment and to generate an action signal dependent on the received state information and a policy associated with that agent, the action signal being operable to cause a change in a state of the environment. Each agent is further arranged to generate experience data dependent on the received state information and information conveyed by the action signal. The first subsystem includes a first network interface configured to send said experience data to the second subsystem and to receive policy data from the second subsystem.

Abstract: A deep approximation neural network architecture which extrapolates data over unseen states for demand response applications in order to control distribution systems like product distribution systems of which energy distribution systems, e.g. heat or electrical power distribution, are one example. The method is a model-free control technique mainly in the form of Reinforcement Learning (RL) where a controller learns from interaction with the system to be controlled to control product distributions of which energy distribution systems, e.g. heat or electrical power distribution, are one example.

Abstract: An epilation apparatus includes a support and a glass pad adhered to the support. The glass pad has an exposed roughened surface that, when placed against human skin and manually manipulated in a rotational motion, is adapted to remove hair from the human skin. A method of using the epilation apparatus involves configuring the support such that the roughened surface of the glass pad is placed against human skin that has hair and manually manipulating the support in a rotational motion such the glass pad removes the hair from the human skin.

Abstract: The present invention relates to compounds and compositions for use in the treatment or prevention of retroviral infections in felines, in particular cats, and to the use of said derivatives for the manufacture of a medicament for the treatment or prevention of feline leukemia virus (FeLV) infections occurring alone or together with feline immunodeficiency virus (FIV) infections in cats.