| 2025 | ICML | Feature learning from non-Gaussian inputs: the case of Independent Component Analysis in high dimensions. | Fabiola Ricci, Lorenzo Bardone, Sebastian Goldt |
| 2024 | ICML | Sliding Down the Stairs: How Correlated Latent Variables Accelerate Learning with Neural Networks. | Lorenzo Bardone, Sebastian Goldt |
| 2023 | ICML | Neural networks trained with SGD learn distributions of increasing complexity. | Maria Refinetti, Alessandro Ingrosso, Sebastian Goldt |
| 2023 | UAI | Quantifying lottery tickets under label noise: accuracy, calibration, and complexity. | Viplove Arora, Daniele Irto, Sebastian Goldt, Guido Sanguinetti |
| 2022 | ICML | Maslow's Hammer in Catastrophic Forgetting: Node Re-Use vs. Node Activation. | Sebastian Lee, Stefano Sarao Mannelli, Claudia Clopath, Sebastian Goldt, Andrew M. Saxe |
| 2022 | ICML | The dynamics of representation learning in shallow, non-linear autoencoders. | Maria Refinetti, Sebastian Goldt |
| 2021 | ICML | Continual Learning in the Teacher-Student Setup: Impact of Task Similarity. | Sebastian Lee, Sebastian Goldt, Andrew M. Saxe |
| 2021 | ICML | Align, then memorise: the dynamics of learning with feedback alignment. | Maria Refinetti, Stphane d'Ascoli, Ruben Ohana, Sebastian Goldt |
| 2021 | ICML | Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed. | Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborov |