Alfredo Reichlin

According to our database, Alfredo Reichlin authored at least 10 papers between 2022 and 2024.

Collaborative distances:

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

2024

Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks.

Alfredo Reichlin, Gustaf Tegnér, Miguel Vasco, Hang Yin, Mårten Björkman, Danica Kragic

CoRR, 2024

Model-based reinforcement learning for protein backbone design.

Frederic Renard, Cyprien Courtot, Alfredo Reichlin, Oliver Bent

CoRR, 2024

Goal-Conditioned Offline Reinforcement Learning via Metric Learning.

Alfredo Reichlin, Miguel Vasco, Hang Yin, Danica Kragic

CoRR, 2024

2023

Learning Geometric Representations of Objects via Interaction.

Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin, Anastasiia Varava, Danica Kragic

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Elastic Context: Encoding Elasticity for Data-driven Models of Textiles Elastic Context: Encoding Elasticity for Data-driven Models of Textiles.

Alberta Longhini, Marco Moletta, Alfredo Reichlin, Michael C. Welle, Alexander Kravberg, Yufei Wang, David Held, Zackory Erickson, Danica Kragic

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

EDO-Net: Learning Elastic Properties of Deformable Objects from Graph Dynamics.

Alberta Longhini, Marco Moletta, Alfredo Reichlin, Michael C. Welle, David Held, Zackory Erickson, Danica Kragic

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Mental Face Image Retrieval Based on a Closed-Loop Brain-Computer Interface.

Nona Rajabi, Charles Chernik, Alfredo Reichlin, Farzaneh Taleb, Miguel Vasco, Ali Ghadirzadeh, Mårten Björkman, Danica Kragic

Proceedings of the Augmented Cognition, 2023

2022

Elastic Context: Encoding Elasticity for Data-driven Models of Textiles.

Alberta Longhini, Marco Moletta, Alfredo Reichlin, Michael C. Welle, Alexander Kravberg, Yufei Wang, David Held, Zackory Erickson, Danica Kragic

CoRR, 2022

On the Subspace Structure of Gradient-Based Meta-Learning.

Gustaf Tegnér, Alfredo Reichlin, Hang Yin, Mårten Björkman, Danica Kragic

CoRR, 2022

Back to the Manifold: Recovering from Out-of-Distribution States.

Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin, Ali Ghadirzadeh, Danica Kragic

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022