Sotabase

Career

· Chapter Head, ASCINA - Austrian Scientists & Scholars in North America2022–
· Research Associate and Co-PI, Harvard University2020–
· Visiting Scholar, Stanford University2020–
· Course Instructor, OpenLabs Kumasi Campus2009–2009
· Volunteer, Melbourne Holocaust Museum2008–2009
· Coordinator Australia, Austrian Service Abroad2006–2010
· Industry Position, ARM
· Graduate Student, Cambridge University
· Intern/Researcher, European Space Agency
· Industry Position, IBM Research
· Graduate Student, University of Oxford

Publications (48)

Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data
arXiv.org · 2024
108
cited
Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating World
arXiv.org · 2024
37
cited
Associations of event-related brain potentials and Alzheimer’s disease severity: A longitudinal study
Progress in Neuro-psychopharmacology and Biological Psychiatry · 2019
34
cited
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning
International Conference on Machine Learning · 2022
25
cited
Reinforcement Learning of Sequential Price Mechanisms
AAAI Conference on Artificial Intelligence · 2020
20
cited
Learning Stackelberg Equilibria in Sequential Price Mechanisms
2021
11
cited
Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning
Adaptive Agents and Multi-Agent Systems · 2023
10
cited
Learning Stackelberg Equilibria and Applications to Economic Design Games
arXiv.org · 2022
8
cited
Revenue Maximization for Market Intermediation with Correlated Priors
Algorithmic Game Theory · 2016
7
cited
Multi-unit Bilateral Trade
AAAI Conference on Artificial Intelligence · 2018
6
cited
Bayesian Gaussian Process Classification from Event-Related Brain Potentials in Alzheimer's Disease
Conference on Artificial Intelligence in Medicine in Europe · 2017
5
cited
CrowdPlay: Crowdsourcing Human Demonstrations for Offline Learning
International Conference on Learning Representations · 2022
5
cited
Riemannian tangent space mapping and elastic net regularization for cost-effective EEG markers of brain atrophy in Alzheimer's disease
Neural Information Processing Systems · 2017
5
cited
A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters
J. Bioinform. Comput. Biol. · 2016
4
cited
Reinforcement Learning of Simple Indirect Mechanisms
arXiv.org · 2020
4
cited
Stackelberg POMDP: A Reinforcement Learning Approach for Economic Design
2022
4
cited
On the Complexity of Optimal Correlated Auctions and Reverse Auctions
Adaptive Agents and Multi-Agent Systems · 2018
3
cited
Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track
arXiv.org · 2025
3
cited
Collaboration Promotes Group Resilience in Multi-Agent AI
2021
2
cited
Reverse auctions are different from auctions
Information Processing Letters · 2019
2
cited
Sotabase
Matthias Gerstgrasser | Researcher Profile | Sotabase | Sotabase