(ongoing) Vera Luksen, Breeding Program Optimization via Offline Reinforcement Learning, TU Eindhoven, in collaboration with Wageningen University & Research
(ongoing) Robert Smolders, Uncertainty Estimation for Offline Reinforcement Learning, TU Eindhoven
(ongoing) Thomas Bosch, Fine-Tuning of Foundational Vision Models, TU Eindhoven, in collaboration with VBTI
(2024) Yana Stoyanova, Model Transfer for Offline Reinforcement Learning, TU Eindhoven
(2024) Ivan Knunyants, Algorithm-hardware co-optimization for Transformers, TU Eindhoven, in collaboration with imec
(2024) Nicholas Kölln, Offline Reinforcement Learning via Transformers, TU Eindhoven
(2023) Maiko Bergman, Offline Reinforcement Learning, TU Eindhoven
(2023) Cas Teeuwen, Delivery Planning via Reinforcement Learning, TU Eindhoven, in collaboration with Datacation
(2023) Ibrahim El Garmouhi, Robust Counterfactual Model Explanation for Patient-Centric Life-style Recommendation on the Cloud, TU Eindhoven, in collaboration with dr. Mostafa Kia
(2022) Youri Vis, Effective Sampling in Intrinsically Motivated Reinforcement Learning, TU Eindhoven
(2022) Jeroen Albrechts, Hyperparameter Optimization via Model-Based Reinforcement Learning, TU Eindhoven
(2022) Mathijs Boezer, FastDTI: Drug-Target Interaction Prediction using
Multimodality and Transformers, TU Eindhoven, Published at NLDL 2023
(2022) Çağla Sözen, A comparative study on Unsupervised Deep Learning Methods for X-Ray Image denoising with Multi-Image Self2Self and Single Frequency, Denoising, TU Eindhoven, in collaboration with Philips Research
(2021) Stef Creemers, Balancing Efficiency and Fairness on Ride-Hailing Platforms via Reinforcement Learning, TU Eindhoven
(2021) Zian Fang, Long- and Short-term Sequential Recommendation with Enhanced Temporal Self-attention, TU Eindhoven
(2021) Huiyao Wu, MuseBar: Alleviating Posterior Collapse in VAE Towards Music Generation, TU Eindhoven, Published at IDA 2022
(2021) Erik Ussin, Enhanced Soft Actor Critic for off-policy continuous control
(2019) Alper Bate, Topic-Sensitive Abstractive Text Summarization using a Variational Autoencoder
(2019) Hermann Foot, Adaptive Packing Optimization using Reinforcement and Imitation Learning
(2017) Ekaterina Dolgovykh, Factorization Machines models for Click-through Rate prediction under data sparsity, in collaboration with XING
(2013) Mario Herdt, Personalized Diverse Recommendations, TU Darmstadt
Bachelor Thesis
(ongoing) Jagoda Nawrat, Adapting Fairness-Aware Datasets for Sequential Use with Group-based Metrics, TU Eindhoven
(ongoing) Arina Crăciun, Adapting Fairness-Aware Datasets for Sequential Use with Individual Metrics, TU Eindhoven
(ongoing) Daniel Osman, Pseudo-Labeling for Scalable and Streamlined Annotations, TU Eindhoven, in collaboration with VBTI
(2024) Kiril Iliev, Active Reinforcement Learning Sampling Approach, TU Eindhoven, in collaboration with VBTI
(2024) Alessandro Preiti, Learn how to Learn: Reinforcement Active Learning for Object Detection, TU Eindhoven, in collaboration with VBTI
(2024) Pradyut Nair, Model-based Offline Reinforcement Learning, TU Eindhoven
(2022) Yana Stoyanova, Comparison Between Various Ensemble Uncertainty Quantification
Methods in Regression Tasks, TU Eindhoven, Published at AAAI 2023
(2022) Lieve Göbbels, Unreliable Uncertainty: How Bayesian Non-identifiability Influences the Performance of Uncertainty Quantification Methods in the Context of Reinforcement Learning, TU Eindhoven
(2016) Akath Singh Dua, Sequential Recommendation Systems
(2015) Radhika Gaonkar, MDP-based itinerary recommendation using geo-tagged social media, TU Darmstadt, Published at IDA 2018
(2014) Divya Venugopalan, Tensor Factorization for User Purchase Pattern Recognition, TU Darmstadt
(2014) Qifeng Hu, Recommender Systems and Personalization, TU Darmstadt
