Lorenzo Noci

According to our database, Lorenzo Noci authored at least 17 papers between 2020 and 2024.

Collaborative distances:

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

2024

Understanding and Minimising Outlier Features in Neural Network Training.

Bobby He, Lorenzo Noci, Daniele Paliotta, Imanol Schlag, Thomas Hofmann

CoRR, 2024

Why do Learning Rates Transfer? Reconciling Optimization and Scaling Limits for Deep Learning.

Lorenzo Noci, Alexandru Meterez, Thomas Hofmann, Antonio Orvieto

CoRR, 2024

Super Consistency of Neural Network Landscapes and Learning Rate Transfer.

Lorenzo Noci, Alexandru Meterez, Thomas Hofmann, Antonio Orvieto

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

Understanding and Minimising Outlier Features in Transformer Training.

Bobby He, Lorenzo Noci, Daniele Paliotta, Imanol Schlag, Thomas Hofmann

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

Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit.

Blake Bordelon, Lorenzo Noci, Mufan Bill Li, Boris Hanin, Cengiz Pehlevan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

How Good is a Single Basin?

Kai Lion, Lorenzo Noci, Thomas Hofmann, Gregor Bachmann

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Disentangling Linear Mode-Connectivity.

Gul Sena Altintas, Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

CoRR, 2023

The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit.

Lorenzo Noci, Chuning Li, Mufan Bill Li, Bobby He, Thomas Hofmann, Chris J. Maddison, Daniel M. Roy

CoRR, 2023

The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit.

Lorenzo Noci, Chuning Li, Mufan Bill Li, Bobby He, Thomas Hofmann, Chris J. Maddison, Dan Roy

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers.

Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurélien Lucchi, Thomas Hofmann

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Curious Case of Benign Memorization.

Sotiris Anagnostidis, Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning.

Sanghwan Kim, Lorenzo Noci, Antonio Orvieto, Thomas Hofmann

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse.

Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurélien Lucchi

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

How Tempering Fixes Data Augmentation in Bayesian Neural Networks.

Gregor Bachmann, Lorenzo Noci, Thomas Hofmann

Proceedings of the International Conference on Machine Learning, 2022

2021

Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect.

Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Precise characterization of the prior predictive distribution of deep ReLU networks.

Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Adversarial Learning for Debiasing Knowledge Graph Embeddings.

Mario Arduini, Lorenzo Noci, Federico Pirovano, Ce Zhang, Yash Raj Shrestha, Bibek Paudel

CoRR, 2020