Optimality of the final model found via Stochastic Gradient Descent. - Andrea Schioppa (CoRR, 2018)

Learning to Transport with Neural Networks. - Andrea Schioppa (CoRR, 2019)

Distributed Function Minimization in Apache Spark. - Andrea Schioppa (CoRR, 2019)

Controlling Machine Translation for Multiple Attributes with Additive Interventions. - Andrea Schioppa; David Vilar; Artem Sokolov; Katja Filippova (EMNLP (1), 2021)

Scaling Up Influence Functions. - Andrea Schioppa; Polina Zablotskaia; David Vilar; Artem Sokolov (AAAI, 2022)

Theoretical and Practical Perspectives on what Influence Functions Do. - Andrea Schioppa; Katja Filippova; Ivan Titov 001; Polina Zablotskaia (NeurIPS, 2023)

Cross-Lingual Supervision improves Large Language Models Pre-training. - Andrea Schioppa; Xavier Garcia; Orhan Firat (CoRR, 2023)

Stacking Diverse Architectures to Improve Machine Translation. - Andrea Schioppa; Nal Kalchbrenner (Trans. Mach. Learn. Res., 2023)

Efficient Sketches for Training Data Attribution and Studying the Loss Landscape. - Andrea Schioppa (NeurIPS, 2024)

Gradient Sketches for Training Data Attribution and Studying the Loss Landscape. - Andrea Schioppa (CoRR, 2024)

Model Integrity when Unlearning with T2I Diffusion Models. - Andrea Schioppa; Emiel Hoogeboom; Jonathan Heek (CoRR, 2024)