Magda Gregorova

17 papers A 1C 1Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	An Investigative Study Exploring Machine Learning Approaches for Optimizing Deep Brain Stimulation Programming. MDIS Esther Ademola, Martin Reich, Magda Gregorova
2024	J	`jnl`	Discrete Graph Auto-Encoder. Trans. Mach. Learn. Res. Yoann Boget, Magda Gregorova, Alexandros Kalousis
2024	J	`jnl`	Generative Example-Based Explanations: Bridging the Gap between Generative Modeling and Explainability. CoRR Philipp Väth, Alexander M. Frühwald, Benjamin Paassen, Magda Gregorova
2024	J	`jnl`	GradCheck: Analyzing classifier guidance gradients for conditional diffusion sampling. CoRR Philipp Väth, Alexander M. Frühwald, Benjamin Paassen, Magda Gregorova
2023	—	`conf`	Diffusion-Based Visual Counterfactual Explanations - Towards Systematic Quantitative Evaluation. PKDD/ECML Workshops (3) Philipp Väth, Alexander M. Frühwald, Benjamin Paassen, Magda Gregorova
2023	J	`jnl`	Diffusion-based Visual Counterfactual Explanations - Towards Systematic Quantitative Evaluation. CoRR Philipp Väth, Alexander M. Frühwald, Benjamin Paaßen, Magda Gregorova
2023	J	`jnl`	Vector-Quantized Graph Auto-Encoder. CoRR Yoann Boget, Magda Gregorova, Alexandros Kalousis
2022	J	`jnl`	GrannGAN: Graph annotation generative adversarial networks. CoRR Yoann Boget, Magda Gregorova, Alexandros Kalousis
2022	C	`conf`	Graph annotation generative adversarial networks. ACML Yoann Boget, Magda Gregorova, Alexandros Kalousis
2021	J	`jnl`	Permutation Equivariant Generative Adversarial Networks for Graphs. CoRR Yoann Boget, Magda Gregorova, Alexandros Kalousis
2020	J	`jnl`	Lifelong generative modeling. Neurocomputing Jason Ramapuram, Magda Gregorova, Alexandros Kalousis
2019	J	`jnl`	Sparse Learning for Variable Selection with Structures and Nonlinearities. CoRR Magda Gregorova
2018	J	`jnl`	Continual Classification Learning Using Generative Models. CoRR Frantzeska Lavda, Jason Ramapuram, Magda Gregorova, Alexandros Kalousis
2018	A	`conf`	Structured nonlinear variable selection. UAI Magda Gregorova, Alexandros Kalousis, Stéphane Marchand-Maillet
2017	J	`jnl`	Forecasting and Granger Modelling with Non-linear Dynamical Dependencies. CoRR Magda Gregorova, Alexandros Kalousis, Stéphane Marchand-Maillet
2017	J	`jnl`	Lifelong Generative Modeling. CoRR Jason Ramapuram, Magda Gregorova, Alexandros Kalousis
2015	J	`jnl`	Learning vector autoregressive models with focalised Granger-causality graphs. CoRR Magda Gregorova, Alexandros Kalousis, Stéphane Marchand-Maillet, Jun Wang