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Ðorðe Miladinovic
Person information
- unicode name: Ðorðe Miladinović
- affiliation: ETH Zurich, Department of Computer Science, Switzerland
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2020 – today
- 2022
- [c8]João B. S. Carvalho, João A. Santinha, Djordje Miladinovic, Carlos Cotrini, Joachim M. Buhmann:
Holistic Modeling In Medical Image Segmentation Using Spatial Recurrence. MIDL 2022: 199-218 - [c7]Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen:
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs. NeurIPS 2022 - [i6]Ðorðe Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen:
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs. CoRR abs/2209.12590 (2022) - 2021
- [b1]Djordje Miladinovic:
On Training Deep Generative Models with Latent Variables. ETH Zurich, Zürich, Switzerland, 2021 - [c6]Ðorðe Miladinovic, Aleksandar Stanic, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann:
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling. ICLR 2021 - [i5]Djordje Miladinovic, Aleksandar Stanic, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann:
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling. CoRR abs/2103.08877 (2021) - [i4]João B. S. Carvalho, João A. Santinha, Djordje Miladinovic, Joachim M. Buhmann:
Spatially Dependent U-Nets: Highly Accurate Architectures for Medical Imaging Segmentation. CoRR abs/2103.11713 (2021)
2010 – 2019
- 2019
- [j1]Ðorðe Miladinovic, Christine Muheim
, Stefan Bauer, Andrea Spinnler, Daniela Noain
SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species. PLoS Comput. Biol. 15(4) (2019) - [c5]Patrick Schwab, Djordje Miladinovic, Walter Karlen
Granger-Causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks. AAAI 2019: 4846-4853 - [c4]Ðorðe Miladinovic, Muhammad Waleed Gondal, Bernhard Schölkopf, Joachim M. Buhmann, Stefan Bauer:
Disentangled State Space Models: Unsupervised Learning of dynamics across Heterogeneous Environments. DGS@ICLR 2019 - [c3]Raphael Suter, Ðorðe Miladinovic, Bernhard Schölkopf, Stefan Bauer:
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness. ICML 2019: 6056-6065 - [c2]Muhammad Waleed Gondal, Manuel Wuthrich, Djordje Miladinovic, Francesco Locatello, Martin Breidt, Valentin Volchkov, Joel Akpo, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer:
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset. NeurIPS 2019: 15714-15725 - [i3]Ðorðe Miladinovic, Muhammad Waleed Gondal, Bernhard Schölkopf, Joachim M. Buhmann, Stefan Bauer:
Disentangled State Space Representations. CoRR abs/1906.03255 (2019) - [i2]Muhammad Waleed Gondal, Manuel Wüthrich, Ðorðe Miladinovic, Francesco Locatello, Martin Breidt, Valentin Volchkov, Joel Akpo, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer:
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset. CoRR abs/1906.03292 (2019) - 2018
- [i1]Raphael Suter, Ðorðe Miladinovic, Stefan Bauer, Bernhard Schölkopf:
Interventional Robustness of Deep Latent Variable Models. CoRR abs/1811.00007 (2018) - 2017
- [c1]Stefan Bauer, Nico S. Gorbach, Ðorðe Miladinovic, Joachim M. Buhmann:
Efficient and Flexible Inference for Stochastic Systems. NIPS 2017: 6988-6998
Coauthor Index
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