Home  | News

23.05.2023

Tiny logo
Teaser image to MCML at PAKDD 2023

MCML at PAKDD 2023

Two Accepted Papers

27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Osaka, Japan, May 25-28, 2023

We are happy to announce that MCML researchers have contributed a total of 2 papers to PAKDD 2023. Congrats to our researchers!

Main Track (2 papers)

T. WeberM. IngrischB. BischlD. Rügamer
Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis.
PAKDD 2023 - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Osaka, Japan, May 25-28, 2023. DOI

D. WinkelN. StraußM. SchubertY. MaT. Seidl
Constrained Portfolio Management using Action Space Decomposition for Reinforcement Learning.
PAKDD 2023 - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Osaka, Japan, May 25-28, 2023. DOI

#research #top-tier-work #bischl #ingrisch #ruegamer #schubert #seidl #tresp
Subscribe to RSS News feed

Related

Link to Zigzag Your Way to Faster, Smarter AI Image Generation

20.11.2025

Zigzag Your Way to Faster, Smarter AI Image Generation

ZigMa, introduced by Björn Ommer’s group at ECCV 24, improves high-res AI image and video generation with fast, memory-efficient zigzag scanning.

Link to Anne-Laure Boulesteix Among the World’s Most Cited Researchers

13.11.2025

Anne-Laure Boulesteix Among the World’s Most Cited Researchers

MCML PI Anne‑Laure Boulesteix named Highly Cited Researcher 2025 for cross-field work, among 17 LMU scholars recognized globally.

Link to Björn Ommer Featured in Frankfurter Rundschau

13.11.2025

Björn Ommer Featured in Frankfurter Rundschau

Björn Ommer highlights how Google’s new AI search mode impacts publishers, content visibility, and the diversity of online information.

Link to Fabian Theis Among the World’s Most Cited Researchers

13.11.2025

Fabian Theis Among the World’s Most Cited Researchers

Fabian Theis is named a Highly Cited Researcher 2025 for his work in mathematical modeling of biological systems.

Link to Explaining AI Decisions: Shapley Values Enable Smart Exosuits

13.11.2025

Explaining AI Decisions: Shapley Values Enable Smart Exosuits

AI meets wearable robotics: MCML and Harvard researchers make exosuits smarter and safer with explainable optimization, presented at ECML-PKDD 2025.

Back to Top