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2020 – today
- 2024
[j4]Marius Benkert
, Michael Heroth, Rainer Herrler, Magda Gregorová, Helmut C. Schmid:
Variational autoencoder-based techniques for a streamlined cross-topology modeling and optimization workflow in electrical drives. Auton. Intell. Syst. 4(1): 8 (2024)- [j3]Yoann Boget, Magda Gregorova, Alexandros Kalousis:
Discrete Graph Auto-Encoder. Trans. Mach. Learn. Res. 2024 (2024) - [i14]Philipp Väth, Alexander M. Frühwald, Benjamin Paassen, Magda Gregorova:
GradCheck: Analyzing classifier guidance gradients for conditional diffusion sampling. CoRR abs/2406.17399 (2024) - 2023
- [i13]Yoann Boget, Magda Gregorova, Alexandros Kalousis:
Vector-Quantized Graph Auto-Encoder. CoRR abs/2306.07735 (2023) - [i12]Philipp Väth, Alexander M. Frühwald, Benjamin Paaßen, Magda Gregorova:
Diffusion-based Visual Counterfactual Explanations - Towards Systematic Quantitative Evaluation. CoRR abs/2308.06100 (2023) - 2022
- [c6]Yoann Boget, Magda Gregorova, Alexandros Kalousis:
Graph annotation generative adversarial networks. ACML 2022: 16 - [i11]Yoann Boget, Magda Gregorova, Alexandros Kalousis:
GrannGAN: Graph annotation generative adversarial networks. CoRR abs/2212.00449 (2022) - 2021
- [i10]Magda Gregorová, Marc Desaules, Alexandros Kalousis:
Learned transform compression with optimized entropy encoding. CoRR abs/2104.03305 (2021) - [i9]Yoann Boget, Magda Gregorova, Alexandros Kalousis:
Permutation Equivariant Generative Adversarial Networks for Graphs. CoRR abs/2112.03621 (2021) - 2020
- [j2]Frantzeska Lavda, Magda Gregorová, Alexandros Kalousis:
Data-Dependent Conditional Priors for Unsupervised Learning of Multimodal Data. Entropy 22(8): 888 (2020) - [j1]Jason Ramapuram, Magda Gregorova, Alexandros Kalousis:
Lifelong generative modeling. Neurocomputing 404: 381-400 (2020) - [c5]Frantzeska Lavda, Magda Gregorová, Alexandros Kalousis:
Improving VAE Generations of Multimodal Data Through Data-Dependent Conditional Priors. ECAI 2020: 1254-1261
2010 – 2019
- 2019
- [i8]Magda Gregorova:
Sparse Learning for Variable Selection with Structures and Nonlinearities. CoRR abs/1903.10978 (2019) - [i7]Frantzeska Lavda, Magda Gregorová, Alexandros Kalousis:
Improving VAE generations of multimodal data through data-dependent conditional priors. CoRR abs/1911.10885 (2019) - 2018
- [c4]Magda Gregorová, Jason Ramapuram, Alexandros Kalousis, Stéphane Marchand-Maillet:
Large-Scale Nonlinear Variable Selection via Kernel Random Features. ECML/PKDD (2) 2018: 177-192 - [c3]Magda Gregorova, Alexandros Kalousis, Stéphane Marchand-Maillet:
Structured nonlinear variable selection. UAI 2018: 23-32 - [i6]Magda Gregorová, Jason Ramapuram, Alexandros Kalousis, Stéphane Marchand-Maillet:
Large-scale Nonlinear Variable Selection via Kernel Random Features. CoRR abs/1804.07169 (2018) - [i5]Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet:
Structured nonlinear variable selection. CoRR abs/1805.06258 (2018) - [i4]Frantzeska Lavda, Jason Ramapuram, Magda Gregorova, Alexandros Kalousis:
Continual Classification Learning Using Generative Models. CoRR abs/1810.10612 (2018) - 2017
- [c2]Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet:
Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks. ACML 2017: 161-176 - [c1]Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet:
Forecasting and Granger Modelling with Non-linear Dynamical Dependencies. ECML/PKDD (2) 2017: 544-558 - [i3]Jason Ramapuram, Magda Gregorova, Alexandros Kalousis:
Lifelong Generative Modeling. CoRR abs/1705.09847 (2017) - [i2]Magda Gregorova, Alexandros Kalousis, Stéphane Marchand-Maillet:
Forecasting and Granger Modelling with Non-linear Dynamical Dependencies. CoRR abs/1706.08811 (2017) - 2015
- [i1]Magda Gregorova, Alexandros Kalousis, Stéphane Marchand-Maillet, Jun Wang:
Learning vector autoregressive models with focalised Granger-causality graphs. CoRR abs/1507.01978 (2015)
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