Ablation Studies in Artificial Neural Networks. - Richard Meyes; Melanie Lu; Constantin Waubert de Puiseau; Tobias Meisen (CoRR, 2019)

Under the Hood of Neural Networks: Characterizing Learned Representations by Functional Neuron Populations and Network Ablations. - Richard Meyes; Constantin Waubert de Puiseau; Andres Posada-Moreno; Tobias Meisen (CoRR, 2020)

On reliability of reinforcement learning based production scheduling systems: a comparative survey. - Constantin Waubert de Puiseau; Richard Meyes; Tobias Meisen (J. Intell. Manuf., 2022)

schlably: A Python Framework for Deep Reinforcement Learning Based Scheduling Experiments. - Constantin Waubert de Puiseau; Jannik Peters 002; Christian Dörpelkus; Tobias Meisen (CoRR, 2023)

Curriculum Learning in Job Shop Scheduling using Reinforcement Learning. - Constantin Waubert de Puiseau; Hasan Tercan; Tobias Meisen (CoRR, 2023)

schlably: A Python framework for deep reinforcement learning based scheduling experiments. - Constantin Waubert de Puiseau; Jannik Peters 002; Christian Dörpelkus; Hasan Tercan; Tobias Meisen (SoftwareX, 2023)

Beyond Training: Optimizing Reinforcement Learning Based Job Shop Scheduling Through Adaptive Action Sampling. - Constantin Waubert de Puiseau; Christian Dörpelkus; Jannik Peters 002; Hasan Tercan; Tobias Meisen (CoRR, 2024)

A Survey on Emergent Language. - Jannik Peters 002; Constantin Waubert de Puiseau; Hasan Tercan; Arya Gopikrishnan; Gustavo Adolpho Lucas de Carvalho; Christian Bitter; Tobias Meisen (CoRR, 2024)

Decision Transformer for Enhancing Neural Local Search on the Job Shop Scheduling Problem. - Constantin Waubert de Puiseau; Fabian Wolz; Merlin Montag; Jannik Peters 002; Hasan Tercan; Tobias Meisen (CoRR, 2024)

Emergent language: a survey and taxonomy. - Jannik Peters 002; Constantin Waubert de Puiseau; Hasan Tercan; Arya Gopikrishnan; Gustavo Adolpho Lucas de Carvalho; Christian Bitter; Tobias Meisen (Auton. Agents Multi Agent Syst., 2025)