Home  | News

06.12.2019

Tiny logo
Teaser image to MCML at NeurIPS 2019

Four Accepted Papers (3 Main, and 1 Workshop)

33rd Conference on Neural Information Processing Systems, Vancouver, Canada, Dec 08-14, 2019

We are happy to announce that MCML researchers have contributed a total of 4 papers to NeurIPS 2019: 3 Main, and 1 Workshop papers. Congrats to our researchers!

Main Track (3 papers)

M. Biloš • B. Charpentier • S. Günnemann
Uncertainty on Asynchronous Time Event Prediction.
NeurIPS 2019 - 33rd Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 08-14, 2019. URL

A. Bojchevski • S. Günnemann
Certifiable Robustness to Graph Perturbations.
NeurIPS 2019 - 33rd Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 08-14, 2019. URL

J. Gasteiger • S. Weißenberger • S. Günnemann
Diffusion Improves Graph Learning.
NeurIPS 2019 - 33rd Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 08-14, 2019. URL

Workshops (1 paper)

E. Faerman • O. Voggenreiter • F. Borutta • T. Emrich • M. BerrendorfM. Schubert
Graph Alignment Networks with Node Matching Scores.
Graph Representation Learning @NeurIPS 2019 - Workshop on Graph Representation Learning at the 33rd Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 08-14, 2019. PDF

#research #top-tier-work #guennemann #schubert #seidl #tresp
Subscribe to RSS News feed

Related

Link to Blind Matching – Aligning Images and Text Without Training or Labels

15.01.2026

Blind Matching – Aligning Images and Text Without Training or Labels

CVPR 2025 research from Daniel Cremers’ group shows how images and text can be aligned without training data, labels, or paired examples.

Link to High-Res Images, Less Wait: A Simple Flow for Image Generation

08.01.2026

High-Res Images, Less Wait: A Simple Flow for Image Generation

ECCV 2024 research led by Björn Ommer’s team enables faster high-resolution image generation by boosting diffusion models with flow matching.

Link to

02.01.2026

MCML Researchers in Highly-Ranked Journals

We are excited to announce that MCML researchers have four papers published in highly-ranked journals in 2026.

Link to "See, Don’t Assume": Revealing and Reducing Gender Bias in AI

18.12.2025

"See, Don’t Assume": Revealing and Reducing Gender Bias in AI

ICLR 2025 research led by Zeynep Akata’s team reveals and reduces gender bias in popular vision-language AI models.

Link to Fabian Theis Featured in Handelsblatt on the Future of AI in Precision Medicine

16.12.2025

Fabian Theis Featured in Handelsblatt on the Future of AI in Precision Medicine

MCML PI Fabian Theis discusses AI-driven precision medicine and its growing impact on individualized healthcare and biomedical research.

Back to Top