On the Limitations of Multimodal VAEs. - Imant Daunhawer; Thomas M. Sutter; Kieran Chin-Cheong; Emanuele Palumbo; Julia E. Vogt (ICLR, 2022)

Identifiability Results for Multimodal Contrastive Learning. - Imant Daunhawer; Alice Bizeul; Emanuele Palumbo; Alexander Marx 001; Julia E. Vogt (ICLR, 2023)

MMVAE+: Enhancing the Generative Quality of Multimodal VAEs without Compromises. - Emanuele Palumbo; Imant Daunhawer; Julia E. Vogt (ICLR, 2023)

Effective Bayesian Heteroscedastic Regression with Deep Neural Networks. - Alexander Immer; Emanuele Palumbo; Alexander Marx 001; Julia E. Vogt (NeurIPS, 2023)

Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders. - Emanuele Palumbo; Laura Manduchi; Sonia Laguna; Daphné Chopard; Julia E. Vogt (ICLR, 2024)

From Logits to Hierarchies: Hierarchical Clustering made Simple. - Emanuele Palumbo; Moritz Vandenhirtz; Alain Ryser; Imant Daunhawer; Julia E. Vogt (CoRR, 2024)