Kaitlin Maile

According to our database, Kaitlin Maile authored at least 16 papers between 2017 and 2026.

Collaborative distances:

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

2026

From Words to Amino Acids: Does the Curse of Depth Persist?

Aleena Siji, Amir Mohammad Karimi-Mamaghan, Ferdinand Kapl, Tobias Höppe, Emmanouil Angelis, Andrea Dittadi, Maurice Brenner, Michael Heinzinger, Karl Henrik Johansson, Kaitlin Maile, Johannes von Oswald, Stefan Bauer

CoRR, February, 2026

From Growing to Looping: A Unified View of Iterative Computation in LLMs.

Ferdinand Kapl, Emmanouil Angelis, Kaitlin Maile, Johannes von Oswald, Stefan Bauer

CoRR, February, 2026

Evolution With Purpose: Hierarchy-Informed Optimization of Whole-Brain Models.

Hormoz Shahrzad, Niharika Gajawelli, Kaitlin Maile, Manish Saggar, Risto Miikkulainen

CoRR, February, 2026

2025

Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning.

Seijin Kobayashi, Yanick Schimpf, Maximilian Schlegel, Angelika Steger, Maciej Wolczyk, Johannes von Oswald, Nino Scherrer, Kaitlin Maile, Guillaume Lajoie, Blake A. Richards, Rif A. Saurous, James Manyika, Blaise Agüera y Arcas, Alexander Meulemans, João Sacramento

CoRR, December, 2025

Best Practices For Empirical Meta-Algorithmic Research: Guidelines from the COSEAL Research Network.

Theresa Eimer, Lennart Schäpermeier, André Biedenkapp, Alexander Tornede, Lars Kotthoff, Pieter Leyman, Matthias Feurer, Katharina Eggensperger, Kaitlin Maile, Tanja Tornede, Anna Kozak, Ke Xue, Marcel Wever, Mitra Baratchi, Damir Pulatov, Heike Trautmann, Haniye Kashgarani, Marius Lindauer

CoRR, December, 2025

Do Depth-Grown Models Overcome the Curse of Depth? An In-Depth Analysis.

Ferdinand Kapl, Emmanouil Angelis, Tobias Höppe, Kaitlin Maile, Johannes von Oswald, Nino Scherrer, Stefan Bauer

CoRR, December, 2025

MesaNet: Sequence Modeling by Locally Optimal Test-Time Training.

Johannes von Oswald, Nino Scherrer, Seijin Kobayashi, Luca Versari, Songlin Yang, Maximilian Schlegel, Kaitlin Maile, Yanick Schimpf, Oliver Sieberling, Alexander Meulemans, Rif A. Saurous, Guillaume Lajoie, Charlotte Frenkel, Razvan Pascanu, Blaise Agüera y Arcas, João Sacramento

CoRR, June, 2025

2023

Dynamic Architectural Optimization of Artificial Neural Networks. (Optimisation architecturale des réseaux neuronaux artificiels).

Kaitlin Maile

PhD thesis, 2023

Composable Function-preserving Expansions for Transformer Architectures.

Andrea Gesmundo, Kaitlin Maile

CoRR, 2023

Equivariance-aware Architectural Optimization of Neural Networks.

Kaitlin Maile, Dennis George Wilson, Patrick Forré

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Structural Learning in Artificial Neural Networks: A Neural Operator Perspective.

Kaitlin Maile, Hervé Luga, Dennis George Wilson

Trans. Mach. Learn. Res., 2022

Architectural Optimization over Subgroups for Equivariant Neural Networks.

Kaitlin Maile, Dennis G. Wilson, Patrick Forré

CoRR, 2022

When, where, and how to add new neurons to ANNs.

Kaitlin Maile, Emmanuel Rachelson, Hervé Luga, Dennis George Wilson

Proceedings of the International Conference on Automated Machine Learning, 2022

2021

On Constrained Optimization in Differentiable Neural Architecture Search.

Kaitlin Maile, Erwan Lecarpentier, Hervé Luga, Dennis G. Wilson

CoRR, 2021

2019

Implementing evolutionary optimization to model neural functional connectivity.

Kaitlin Maile, Manish Saggar, Risto Miikkulainen

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019

2017

Effects of Soft Drinks on Resting State EEG and Brain-Computer Interface Performance.

Jianjun Meng, John Mundahl, Taylor D. Streitz, Kaitlin Maile, Nicholas S. Gulachek, Jeffrey He, Bin He

IEEE Access, 2017