74 citations · 272 across the 40 of their papers we have counts for
5 papers · 1 filter
Biologically-Inspired Spatial Neural Networks
Maciej Wołczyk, Jacek Tabor, Marek Śmieja +1
We introduce bio-inspired artificial neural networks consisting of neurons that are additionally characterized by spatial positions. To simulate properties of biological systems we…
Spatial Graph Convolutional Networks
Tomasz Danel, Przemysław Spurek, Jacek Tabor +4
Graph Convolutional Networks (GCNs) have recently become the primary choice for learning from graph-structured data, superseding hash fingerprints in representing chemical compound…
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models
Paweł Morawiecki, Przemysław Spurek, Marek Śmieja +1
We present an efficient technique, which allows to train classification networks which are verifiably robust against norm-bounded adversarial attacks. This framework is built upon…
SeGMA: Semi-Supervised Gaussian Mixture Auto-Encoder
Marek Śmieja, Maciej Wołczyk, Jacek Tabor +1
We propose a semi-supervised generative model, SeGMA, which learns a joint probability distribution of data and their classes and which is implemented in a typical Wasserstein auto…
Hypernetwork functional image representation
Sylwester Klocek, Łukasz Maziarka, Maciej Wołczyk +3
Motivated by the human way of memorizing images we introduce their functional representation, where an image is represented by a neural network. For this purpose, we construct a hy…