Mathijs Mul

According to our database, Mathijs Mul authored at least 7 papers between 2019 and 2020.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2020

Compositionality Decomposed: How do Neural Networks Generalise?

Dieuwke Hupkes, Verna Dankers, Mathijs Mul, Elia Bruni

J. Artif. Intell. Res., 2020

Compositionality Decomposed: How do Neural Networks Generalise? (Extended Abstract).

Dieuwke Hupkes, Verna Dankers, Mathijs Mul, Elia Bruni

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Learning to Request Guidance in Emergent Communication.

Benjamin Kolb, Leon Lang, Henning Bartsch, Arwin Gansekoele, Raymond Koopmanschap, Leonardo Romor, David Speck, Mathijs Mul, Elia Bruni

CoRR, 2019

The compositionality of neural networks: integrating symbolism and connectionism.

Dieuwke Hupkes, Verna Dankers, Mathijs Mul, Elia Bruni

CoRR, 2019

Mastering emergent language: learning to guide in simulated navigation.

Mathijs Mul, Diane Bouchacourt, Elia Bruni

CoRR, 2019

Siamese recurrent networks learn first-order logic reasoning and exhibit zero-shot compositional generalization.

Mathijs Mul, Willem H. Zuidema

CoRR, 2019

Learning to request guidance in emergent language.

Benjamin Kolb, Leon Lang, Henning Bartsch, Arwin Gansekoele, Raymond Koopmanschap, Leonardo Romor, David Speck, Mathijs Mul, Elia Bruni

Proceedings of the Beyond Vision and LANguage: inTEgrating Real-world kNowledge, 2019