ICST 2024 (series) / Research Papers /
Learning Environment Models with Continuous Stochastic Dynamics - with an Application to Deep RL Testing
This program is tentative and subject to change.
Fri 31 May 2024 12:00 - 12:20 at Room 2 - Testing with and for Deep and Reinforcement Learning
This program is tentative and subject to change.
Fri 31 MayDisplayed time zone: Eastern Time (US & Canada) change
Fri 31 May
Displayed time zone: Eastern Time (US & Canada) change
11:00 - 12:20 | |||
11:00 20mResearch paper | METAL: Metamorphic Testing Framework for Analyzing Large-Language Model Qualities Research Papers Sangwon Hyun University of Adelaide, Mingyu Guo , Muhammad Ali Babar School of Computer Science, The University of Adelaide | ||
11:20 20mIndustry talk | End-to-end RPA-like testing using reinforcement learning Industry Ciprian Paduraru University of Bucharest, Rares Cristea University of Bucharest, Alin Stefanescu University of Bucharest | ||
11:40 20mResearch paper | Spectral Analysis of the Relation between Deep Learning Faults and Neural Activation Values Research Papers | ||
12:00 20mResearch paper | Learning Environment Models with Continuous Stochastic Dynamics - with an Application to Deep RL Testing Research Papers Martin Tappler TU Graz; Silicon Austria Labs, Edi Muskardin , Bernhard Aichernig Graz University of Technology, Bettina Könighofer | ||