Reducing Overestimation Bias in Multi-Agent Domains Using Double Centralized Critics. - Johannes Ackermann; Volker Gabler; Takayuki Osa; Masashi Sugiyama (CoRR, 2019)

Convolutional Neural Network Based Blind Estimation of Generalized Mutual Information for Optical Communication. - Johannes Ackermann; Maximilian Schädler; Christian Blümm (ECOC, 2020)

Impact of Acoustic and Interactive Disruptive Factors during Robot-Assisted Surgery - A Virtual Surgical Training Model. - Magret Krüger; Johannes Ackermann; Daniar Osmonov; Veronika Günther; Dirk Bauerschlag; Johannes Hensler; Jan-Hendrik Egberts; Sebastian Lippross; Georgios Gitas; Thomas Becker 007; Nicolai Maass; Klaus-Peter Jünemann; et al. (Sensors, 2020)

Unsupervised Task Clustering for Multi-task Reinforcement Learning. - Johannes Ackermann; Oliver Richter; Roger Wattenhofer (ECML/PKDD (1), 2021)

High-Resolution Image Editing via Multi-Stage Blended Diffusion. - Johannes Ackermann; Minjun Li (CoRR, 2022)

Offline Reinforcement Learning from Datasets with Structured Non-Stationarity. - Johannes Ackermann; Takayuki Osa; Masashi Sugiyama (RLJ, 2024)

Leveraging Domain-Unlabeled Data in Offline Reinforcement Learning across Two Domains. - Soichiro Nishimori; Xin-Qiang Cai; Johannes Ackermann; Masashi Sugiyama (CoRR, 2024)

Recursive Reward Aggregation. - Yuting Tang; Yivan Zhang; Johannes Ackermann; Yu-Jie Zhang; Soichiro Nishimori; Masashi Sugiyama (CoRR, 2025)

Off-Policy Corrected Reward Modeling for Reinforcement Learning from Human Feedback. - Johannes Ackermann; Takashi Ishida 001; Masashi Sugiyama (CoRR, 2025)