SchNetPack: A Deep Learning Toolbox For Atomistic Systems

We have illustrated this principle by showing how linear logic focusing and logical equivalences can account for object-level proof systems based on sequent calculus, natural

Local learning algorithms can require a number of training examples exponential in the input dimension to obtain a given generalization error.... Curse

• a novel training process is introduced, based on a single image (acquired at a reference pose), which includes the fast creation of a dataset using a simulator allowing for

For instance, our approach already provides a generic stub of proxy agent resulted from the development of the ACE4SD, and consisting of several facilities such as means for

After analyzing several approaches on self-adaptive software systems and identifying adaptation properties, we propose a process for evaluating self-adaptation with which

In our poster, we will introduce new datasets in propositional logic and first-order logic that can be used for learning to rea- son, and present some initial results on systems

Keywords: neo-fuzzy autoencoder, deep learning network, neo-fuzzy neuron, fast learning algorithm, data compression..

While MD algorithms are able to produce reasonable results in case of user or item cold-start and can deal with a system cold-start as well, experiments have shown that CF