Neural Symbolic Regression that scales. - Luca Biggio; Tommaso Bendinelli; Alexander Neitz; Aurélien Lucchi; Giambattista Parascandolo (ICML, 2021)

Dynaformer: A Deep Learning Model for Ageing-aware Battery Discharge Prediction. - Luca Biggio; Tommaso Bendinelli; Chetan S. Kulkarni; Olga Fink (CoRR, 2022)

Controllable Neural Symbolic Regression. - Tommaso Bendinelli; Luca Biggio; Pierre-Alexandre Kamienny (ICML, 2023)

Optimizing IoT-Based Asset and Utilization Tracking: Efficient Activity Classification with MINIROCKET on Resource-Constrained Devices. - Marco Giordano; Silvano Cortesi; Michele Crabolu; Lavinia Pedrollo; Giovanni Bellusci; Tommaso Bendinelli; Engin Türetken; L. Andrea Dunbar; Michele Magno (WF-IoT, 2023)

Gemtelligence: Accelerating Gemstone classification with Deep Learning. - Tommaso Bendinelli; Luca Biggio; Daniel Nyfeler; Abhigyan Ghosh; Peter Tollan; Moritz Alexander Kirschmann; Olga Fink (CoRR, 2023)

Exploring LLM Agents for Cleaning Tabular Machine Learning Datasets. - Tommaso Bendinelli; Artur Dox; Christian Holz 001 (CoRR, 2025)