Luca Biggio

29 papers A* 7B 1Journal 19Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Biased Generalization in Diffusion Models.
CoRR
Jerome Garnier-Brun, Luca Biggio, Davide Beltrame, Marc Mézard, Luca Saglietti
2025 A* conf
Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward Layers.
ICML
Freya Behrens, Luca Biggio, Lenka Zdeborová
2025 J jnl
On the Bias of Next-Token Predictors Toward Systematically Inefficient Reasoning: A Shortest-Path Case Study.
CoRR
Riccardo Alberghi, Elizaveta Demyanenko, Luca Biggio, Luca Saglietti
2024 J jnl
Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens.
CoRR
Vittorio Erba, Emanuele Troiani, Luca Biggio, Antoine Maillard, Lenka Zdeborová
2024 J jnl
Understanding Counting in Small Transformers: The Interplay between Attention and Feed-Forward Layers.
CoRR
Freya Behrens, Luca Biggio, Lenka Zdeborová
2023 A* conf
An SDE for Modeling SAM: Theory and Insights.
ICML
Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Frank Norbert Proske, Hans Kersting, Aurélien Lucchi
2023 J jnl
An SDE for Modeling SAM: Theory and Insights.
CoRR
Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Frank Norbert Proske, Hans Kersting, Aurélien Lucchi
2023 A* conf
Controllable Neural Symbolic Regression.
ICML
Tommaso Bendinelli, Luca Biggio, Pierre-Alexandre Kamienny
2023 J jnl
Controllable Neural Symbolic Regression.
CoRR
Tommaso Bendinelli, Luca Biggio, Pierre-Alexandre Kamienny
2023 A* conf
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers.
NeurIPS
Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurélien Lucchi, Thomas Hofmann
2023 J jnl
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers.
CoRR
Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurélien Lucchi, Thomas Hofmann
2023 A* conf
FIGARO: Controllable Music Generation using Learned and Expert Features.
ICLR
Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hofmann
2023 J jnl
Gemtelligence: Accelerating Gemstone classification with Deep Learning.
CoRR
Tommaso Bendinelli, Luca Biggio, Daniel Nyfeler, Abhigyan Ghosh, Peter Tollan, Moritz Alexander Kirschmann, Olga Fink
2023 J jnl
Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization.
CoRR
Elior Benarous, Sotiris Anagnostidis, Luca Biggio, Thomas Hofmann
2023 B conf
On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics.
IJCNN
Enea Monzio Compagnoni, Anna Scampicchio, Luca Biggio, Antonio Orvieto, Thomas Hofmann, Josef Teichmann
2023 — —
Transformers beyond natural language: a theoretical and empirical investigation.
Luca Biggio
2023 J jnl
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial.
CoRR
Venkat Nemani, Luca Biggio, Xun Huan, Zhen Hu, Olga Fink, Anh Tran, Yan Wang, Xiaoping Du, Xiaoge Zhang, Chao Hu
2022 J jnl
Cosmology from Galaxy Redshift Surveys with PointNet.
CoRR
Sotiris Anagnostidis, Arne Thomsen, Tomasz Kacprzak, Tilman Tröster, Luca Biggio, Alexandre Refregier, Thomas Hofmann
2022 J jnl
Dynaformer: A Deep Learning Model for Ageing-aware Battery Discharge Prediction.
CoRR
Luca Biggio, Tommaso Bendinelli, Chetan S. Kulkarni, Olga Fink
2022 J jnl
FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control.
CoRR
Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hoffman
2022 J jnl
Randomized Signature Layers for Signal Extraction in Time Series Data.
CoRR
Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Thomas Hofmann, Josef Teichmann
2022 A* conf
Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse.
NeurIPS
Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurélien Lucchi
2022 J jnl
Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse.
CoRR
Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurélien Lucchi
2021 J jnl
Neural Symbolic Regression that Scales.
CoRR
Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurélien Lucchi, Giambattista Parascandolo
2021 A* conf
Neural Symbolic Regression that scales.
ICML
Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurélien Lucchi, Giambattista Parascandolo
2021 — conf
Self-supervised pre-training on industrial time-series.
SDS
Luca Biggio, Iason Kastanis
2021 J jnl
Uncertainty-Aware Prognosis via Deep Gaussian Process.
IEEE Access
Luca Biggio, Alexander Wieland, Manuel Arias Chao, Iason Kastanis, Olga Fink
2021 J jnl
Uncertainty-aware Remaining Useful Life predictor.
CoRR
Luca Biggio, Alexander Wieland, Manuel Arias Chao, Iason Kastanis, Olga Fink
2020 J jnl
Prognostics and Health Management of Industrial Assets: Current Progress and Road Ahead.
Frontiers Artif. Intell.
Luca Biggio, Iason Kastanis