← Authors

Julia E Vogt

16 papers · 2021–2025 · 3 conferences · across top CS/AI conferences

Achievements

🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (3) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (14) 💎 Century Club (16) ⚡ Prolific Year (6) ❓ The Questioner 🔥 Unstoppable (5)

Conferences

ICLR (10) ICML (4) MLHC (2)

Top co-authors

Imant Daunhawer (7) Emanuele Palumbo (5) Thomas M. Sutter (3) Laura Manduchi (3) Daphné Chopard (3) Kieran Chin-Cheong (2) Alice Bizeul (2) Alain Ryser (2) Ričards Marcinkevičs (2) Moritz Vandenhirtz (2)

Keywords

causal inference (1) conditional distribution (1) feature map (1) heteroscedastic noise (1) location-scale noise model (1) neural network (1) location-scale model (1)

Papers

Cross-Entropy Is All You Need To Invert the Data Generating Process ICLR 2025
PhenoRAG: Retrieval-Augmented Generation for Efficient Zero-Shot Phenotype Identification in Clinical Reports MLHC 2025
Towards Scalable Newborn Screening: Automated General Movement Assessment in Uncontrolled Settings MLHC 2025
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection ICML 2025
From Logits to Hierarchies: Hierarchical Clustering made Simple ICML 2025
scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data ICML 2025
Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders ICLR 2024
Learning Group Importance using the Differentiable Hypergeometric Distribution ICLR 2023
Identifiability Results for Multimodal Contrastive Learning ICLR 2023
On the Identifiability and Estimation of Causal Location-Scale Noise Models ICML 2023
How robust is unsupervised representation learning to distribution shift? ICLR 2023
MMVAE+: Enhancing the Generative Quality of Multimodal VAEs without Compromises ICLR 2023
On the Limitations of Multimodal VAEs ICLR 2022
A Deep Variational Approach to Clustering Survival Data ICLR 2022
Generalized Multimodal ELBO ICLR 2021
Interpretable Models for Granger Causality Using Self-explaining Neural Networks ICLR 2021