Michael Munn

According to our database, Michael Munn authored at least 15 papers between 2020 and 2025.

Collaborative distances:

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

2025

Equivalence of Context and Parameter Updates in Modern Transformer Blocks.

Adrian Goldwaser, Michael Munn, Javier Gonzalvo, Benoit Dherin

CoRR, November, 2025

Transmuting prompts into weights.

Hanna Mazzawi, Benoit Dherin, Michael Munn, Michael Wunder, Javier Gonzalvo

CoRR, October, 2025

On residual network depth.

Benoit Dherin, Michael Munn

CoRR, October, 2025

Learning without training: The implicit dynamics of in-context learning.

Benoit Dherin, Michael Munn, Hanna Mazzawi, Michael Wunder, Javier Gonzalvo

CoRR, July, 2025

Learning by solving differential equations.

Benoit Dherin, Michael Munn, Hanna Mazzawi, Michael Wunder, Sourabh Medapati, Javier Gonzalvo

CoRR, May, 2025

Training in reverse: How iteration order influences convergence and stability in deep learning.

Benoit Dherin, Benny Avelin, Anders Karlsson, Hanna Mazzawi, Javier Gonzalvo, Michael Munn

CoRR, February, 2025

How iteration composition influences convergence and stability in deep learning.

Benoit Dherin, Benny Avelin, Anders Karlsson, Hanna Mazzawi, Javier Gonzalvo, Michael Munn

Trans. Mach. Learn. Res., 2025

A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints.

Michael Munn, Susan Wei

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Leveraging free energy in pretraining model selection for improved fine-tuning.

Michael Munn, Susan Wei

CoRR, 2024

The Impact of Geometric Complexity on Neural Collapse in Transfer Learning.

Michael Munn, Benoit Dherin, Javier Gonzalvo

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Unified Functional Hashing in Automatic Machine Learning.

Ryan Gillard, Stephen Jonany, Yingjie Miao, Michael Munn, Connal de Souza, Jonathan Dungay, Chen Liang, David R. So, Quoc V. Le, Esteban Real

CoRR, 2023

A margin-based multiclass generalization bound via geometric complexity.

Michael Munn, Benoit Dherin, Javier Gonzalvo

Proceedings of the Topological, 2023

2022

Why neural networks find simple solutions: The many regularizers of geometric complexity.

Benoit Dherin, Michael Munn, Mihaela Rosca, David Barrett

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

The Geometric Occam's Razor Implicit in Deep Learning.

Benoit Dherin, Michael Munn, David G. T. Barrett

CoRR, 2021

2020

COT-GAN: Generating Sequential Data via Causal Optimal Transport.

Tianlin Xu, Li Kevin Wenliang, Michael Munn, Beatrice Acciaio

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020