Emanuele Palumbo

According to our database, Emanuele Palumbo authored at least 10 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

TOAST: Transformer Optimization using Adaptive and Simple Transformations.

Irene Cannistraci, Simone Antonelli, Emanuele Palumbo, Thomas M. Sutter, Emanuele Rodolà, Bastian Rieck, Julia E. Vogt

Trans. Mach. Learn. Res., 2026

Steering Generative Models for Accessibility: EasyRead Image Generation.

Nicolas Dickenmann, Yanis Merzouki, Sonia Laguna, Thy Nowak-Tran, Emanuele Palumbo, Julia E. Vogt, Gerda Binder

Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems, 2026

2025

Hybrid Modeling of Photoplethysmography for Non-invasive Monitoring of Cardiovascular Parameters.

Emanuele Palumbo, Sorawit Saengkyongam, Maria R. Cervera, Jens Behrmann, Andrew C. Miller, Guillermo Sapiro, Christina Heinze-Deml, Antoine Wehenkel

CoRR, November, 2025

Post-hoc Stochastic Concept Bottleneck Models.

Wiktor Jan Hoffmann, Sonia Laguna, Moritz Vandenhirtz, Emanuele Palumbo, Julia E. Vogt

CoRR, October, 2025

From Logits to Hierarchies: Hierarchical Clustering made Simple.

Emanuele Palumbo, Moritz Vandenhirtz, Alain Ryser, Imant Daunhawer, Julia E. Vogt

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders.

Emanuele Palumbo, Laura Manduchi, Sonia Laguna, Daphné Chopard, Julia E. Vogt

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Effective Bayesian Heteroscedastic Regression with Deep Neural Networks.

Alexander Immer, Emanuele Palumbo, Alexander Marx, Julia E. Vogt

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MMVAE+: Enhancing the Generative Quality of Multimodal VAEs without Compromises.

Emanuele Palumbo, Imant Daunhawer, Julia E. Vogt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Identifiability Results for Multimodal Contrastive Learning.

Imant Daunhawer, Alice Bizeul, Emanuele Palumbo, Alexander Marx, Julia E. Vogt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

On the Limitations of Multimodal VAEs.

Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E. Vogt

Proceedings of the Tenth International Conference on Learning Representations, 2022