Daunhawer, Imant

13 publications

ICML 2025 From Logits to Hierarchies: Hierarchical Clustering Made Simple Emanuele Palumbo, Moritz Vandenhirtz, Alain Ryser, Imant Daunhawer, Julia E Vogt

ICML 2025 scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data Olga Ovcharenko, Florian Barkmann, Philip Toma, Imant Daunhawer, Julia E Vogt, Sebastian Schelter, Valentina Boeva

NeurIPSW 2024 Benchmarking Self-Supervised Learning for Single-Cell Data Philip Toma, Olga Ovcharenko, Imant Daunhawer, Julia E Vogt, Florian Barkmann, Valentina Boeva

ICLR 2023 How Robust Is Unsupervised Representation Learning to Distribution Shift? Yuge Shi, Imant Daunhawer, Julia E Vogt, Philip Torr, Amartya Sanyal

ICLR 2023 Identifiability Results for Multimodal Contrastive Learning Imant Daunhawer, Alice Bizeul, Emanuele Palumbo, Alexander Marx, Julia E Vogt

ICLR 2023 MMVAE+: Enhancing the Generative Quality of Multimodal VAEs Without Compromises Emanuele Palumbo, Imant Daunhawer, Julia E Vogt

ICMLW 2022 How Robust Are Pre-Trained Models to Distribution Shift? Yuge Shi, Imant Daunhawer, Julia E Vogt, Philip Torr, Amartya Sanyal

ICMLW 2022 How Robust Are Pre-Trained Models to Distribution Shift? Yuge Shi, Imant Daunhawer, Julia E Vogt, Philip Torr, Amartya Sanyal

ICLRW 2022 MMVAE+: Enhancing the Generative Quality of Multimodal VAEs Without Compromises Emanuele Palumbo, Imant Daunhawer, Julia E Vogt

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

ICLR 2021 Generalized Multimodal ELBO Thomas M. Sutter, Imant Daunhawer, Julia E Vogt

NeurIPSW 2021 On the Limitations of Multimodal VAEs Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E Vogt

NeurIPS 2020 Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence Thomas Sutter, Imant Daunhawer, Julia Vogt