no code implementations • 16 May 2024 • Arwin Gansekoele, Alexios Balatsoukas-Stimming, Tom Brusse, Mark Hoogendoorn, Sandjai Bhulai, Rob van der Mei
As telecommunication systems evolve to meet increasing demands, integrating deep neural networks (DNNs) has shown promise in enhancing performance.
no code implementations • 16 May 2024 • Arwin Gansekoele, Tycho Bot, Rob van der Mei, Sandjai Bhulai, Mark Hoogendoorn
Third, we show that our method scales well to a dataset of over 1000 videos.
no code implementations • 31 Jan 2024 • Yura Perugachi-Diaz, Arwin Gansekoele, Sandjai Bhulai
Finally, we show how refinement of the latents with our best-performing method improves the compression performance on the Tecnick dataset and how it can be deployed to partly move along the rate-distortion curve.
no code implementations • 11 Dec 2019 • Benjamin Kolb, Leon Lang, Henning Bartsch, Arwin Gansekoele, Raymond Koopmanschap, Leonardo Romor, David Speck, Mathijs Mul, Elia Bruni
Previous research into agent communication has shown that a pre-trained guide can speed up the learning process of an imitation learning agent.
no code implementations • WS 2019 • Benjamin Kolb, Leon Lang, Henning Bartsch, Arwin Gansekoele, Raymond Koopmanschap, Leonardo Romor, David Speck, Mathijs Mul, Elia Bruni
Previous research into agent communication has shown that a pre-trained guide can speed up the learning process of an imitation learning agent.