20 citations · 31 across the 4 of their papers we have counts for
5 papers
Neural Arithmetic Units
Andreas Madsen, Alexander Rosenberg Johansen
Neural networks can approximate complex functions, but they struggle to perform exact arithmetic operations over real numbers. The lack of inductive bias for arithmetic operations…
Autoencoding Undirected Molecular Graphs With Neural Networks
Jeppe Johan Waarkjær Olsen, Peter Ebert Christensen, Martin Hangaard Hansen +1
Discrete structure rules for validating molecular structures are usually limited to fulfillment of the octet rule or similar simple deterministic heuristics. We propose a model, in…
Measuring Arithmetic Extrapolation Performance
Andreas Madsen, Alexander Rosenberg Johansen
The Neural Arithmetic Logic Unit (NALU) is a neural network layer that can learn exact arithmetic operations between the elements of a hidden state. The goal of NALU is to learn pe…
Learning when to skim and when to read
Alexander Rosenberg Johansen, Richard Socher
Many recent advances in deep learning for natural language processing have come at increasing computational cost, but the power of these state-of-the-art models is not needed for e…
Neural Machine Translation with Characters and Hierarchical Encoding
Alexander Rosenberg Johansen, Jonas Meinertz Hansen, Elias Khazen Obeid +2
Most existing Neural Machine Translation models use groups of characters or whole words as their unit of input and output. We propose a model with a hierarchical char2word encoder,…