Marissa A. Weis

According to our database, Marissa A. Weis authored at least 12 papers between 2018 and 2026.

Collaborative distances:

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

2026

OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens.

Konstantin F. Willeke, Polina Turishcheva, Alex Gilbert, Goirik Chakrabarty, Hasan A. Bedel, Paul G. Fahey, Yongrong Qiu, Marissa A. Weis, Michaela Vystrcilová, Taliah Muhammad, Lydia Ntanavara, Rachel Froebe, Kayla Ponder, Zheng Huan Tan, Emin Orhan, Erick Cobos, Sophia Sanborn, Katrin Franke, Fabian H. Sinz, Alexander S. Ecker, Andreas S. Tolias

CoRR, April, 2026

Multi-agent cooperation through in-context co-player inference.

Marissa A. Weis, Maciej Wolczyk, Rajai Nasser, Rif A. Saurous, Blaise Agüera y Arcas, João Sacramento, Alexander Meulemans

CoRR, February, 2026

2025

Embedded Universal Predictive Intelligence: a coherent framework for multi-agent learning.

Alexander Meulemans, Rajai Nasser, Maciej Wolczyk, Marissa A. Weis, Seijin Kobayashi, Blake A. Richards, Guillaume Lajoie, Angelika Steger, Marcus Hutter, James Manyika, Rif A. Saurous, João Sacramento, Blaise Agüera y Arcas

CoRR, November, 2025

Hierarchical clustering with maximum density paths and mixture models.

Martin Ritzert, Polina Turishcheva, Laura Hansel, Paul Wollenhaupt, Marissa A. Weis, Alexander S. Ecker

CoRR, March, 2025

2024

Unsupervised Representation Learning for Object-Centric and Neuronal Morphology Modeling

Marissa A. Weis

PhD thesis, 2024

MNIST-Nd: a set of naturalistic datasets to benchmark clustering across dimensions.

Polina Turishcheva, Laura Hansel, Martin Ritzert, Marissa A. Weis, Alexander S. Ecker

CoRR, 2024

2023

Self-Supervised Graph Representation Learning for Neuronal Morphologies.

Marissa A. Weis, Laura Pede, Timo Lüddecke, Alexander S. Ecker

Trans. Mach. Learn. Res., 2023

2021

Benchmarking Unsupervised Object Representations for Video Sequences.

Marissa A. Weis, Kashyap Chitta, Yash Sharma, Wieland Brendel, Matthias Bethge, Andreas Geiger, Alexander S. Ecker

J. Mach. Learn. Res., 2021

Self-supervised Representation Learning of Neuronal Morphologies.

Marissa A. Weis, Laura Pede, Timo Lüddecke, Alexander S. Ecker

CoRR, 2021

2020

Unmasking the Inductive Biases of Unsupervised Object Representations for Video Sequences.

Marissa A. Weis, Kashyap Chitta, Yash Sharma, Wieland Brendel, Matthias Bethge, Andreas Geiger, Alexander S. Ecker

CoRR, 2020

2019

Flexibly Fair Representation Learning by Disentanglement.

Elliot Creager, David Madras, Jörn-Henrik Jacobsen, Marissa A. Weis, Kevin Swersky, Toniann Pitassi, Richard S. Zemel

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Diverse Feature Visualizations Reveal Invariances in Early Layers of Deep Neural Networks.

Santiago A. Cadena, Marissa A. Weis, Leon A. Gatys, Matthias Bethge, Alexander S. Ecker

Proceedings of the Computer Vision - ECCV 2018, 2018