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Tommaso Bendinelli
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2020 – today
- 2023
- [c3]Tommaso Bendinelli, Luca Biggio, Pierre-Alexandre Kamienny:
Controllable Neural Symbolic Regression. ICML 2023: 2063-2077 - [c2]Marco Giordano, Silvano Cortesi, Michele Crabolu, Lavinia Pedrollo, Giovanni Bellusci, Tommaso Bendinelli, Engin Türetken, L. Andrea Dunbar, Michele Magno:
Optimizing IoT-Based Asset and Utilization Tracking: Efficient Activity Classification with MINIROCKET on Resource-Constrained Devices. WF-IoT 2023: 1-8 - [i4]Tommaso Bendinelli, Luca Biggio, Pierre-Alexandre Kamienny:
Controllable Neural Symbolic Regression. CoRR abs/2304.10336 (2023) - [i3]Tommaso Bendinelli, Luca Biggio, Daniel Nyfeler, Abhigyan Ghosh, Peter Tollan, Moritz Alexander Kirschmann, Olga Fink:
Gemtelligence: Accelerating Gemstone classification with Deep Learning. CoRR abs/2306.06069 (2023) - 2022
- [i2]Luca Biggio, Tommaso Bendinelli, Chetan S. Kulkarni, Olga Fink:
Dynaformer: A Deep Learning Model for Ageing-aware Battery Discharge Prediction. CoRR abs/2206.02555 (2022) - 2021
- [c1]Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurélien Lucchi, Giambattista Parascandolo:
Neural Symbolic Regression that scales. ICML 2021: 936-945 - [i1]Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurélien Lucchi, Giambattista Parascandolo:
Neural Symbolic Regression that Scales. CoRR abs/2106.06427 (2021)
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last updated on 2024-06-20 21:29 CEST by the dblp team
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