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Set-to-Sequence Methods in Machine Learning: a Review

v1v2 (latest)

Set-to-Sequence Methods in Machine Learning: a Review

Journal of Artificial Intelligence Research (JAIR), 2021

17 March 2021

Mateusz Jurewicz

Leon Derczynski

ArXiv (abs)PDF HTML Github

Papers citing "Set-to-Sequence Methods in Machine Learning: a Review"

4 / 4 papers shown

Set2Seq Transformer: Temporal and Position-Aware Set Representations for Sequential Multiple-Instance Learning

Set2Seq Transformer: Temporal and Position-Aware Set Representations for Sequential Multiple-Instance Learning

Athanasios Efthymiou

Monika Kackovic

Nachoem Wijnberg

324

0

0

06 Aug 2024

Set Interdependence Transformer: Set-to-Sequence Neural Networks for
Permutation Learning and Structure Prediction

Set Interdependence Transformer: Set-to-Sequence Neural Networks for Permutation Learning and Structure PredictionInternational Joint Conference on Artificial Intelligence (IJCAI), 2022

Mateusz Jurewicz

Leon Derczynski

195

4

0

08 Jun 2022

Towards Improving the Generation Quality of Autoregressive Slot VAEs

Towards Improving the Generation Quality of Autoregressive Slot VAEs

Sanjay Ranka

Anand Rangarajan

284

1

0

03 Jun 2022

Learning Prototype-oriented Set Representations for Meta-Learning

Learning Prototype-oriented Set Representations for Meta-Learning

Mingyuan Zhou

171

27

0

18 Oct 2021

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