Đorđe Miladinović

Associate Fellow, Max Planck Institute for Intelligent Systems, Max-Planck Institute

Joined

March 2019

Names

Đorđe Miladinović (Preferred)

Djordje Miladinovic

Emails

****@ethz.ch (Confirmed)

****@inf.ethz.ch (Confirmed)

****@gmail.com (Confirmed)

****@gsk.com (Confirmed)

Personal Links

DBLP

Career & Education History

Associate Fellow

Max Planck Institute for Intelligent Systems, Max-Planck Institute (tuebingen.mpg.de)

2018 – Present

PhD student

Swiss Federal Institute of Technology (ethz.ch)

2017 – 2021

Advisors, Relations & Conflicts

PhD Advisor

Joachim M. Buhmann

Present

Expertise

Deep Generative Models

Present

Autoregressive Models

Present

Variational Autoencoders

Present

Latent-variable models

Present

Publications

Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs
Đorđe Miladinović, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen
- Published: 31 Oct 2022, Last Modified: 16 Dec 2022
- NeurIPS 2022 Accept
- Readers: Everyone
Holistic Modeling in Medical Image Segmentation Using Spatial Recurrence
João B. S. Carvalho, João Santinha, Đorđe Miladinović, Carlos Cotrini, Joachim M. Buhmann
- Published: 28 Feb 2022, Last Modified: 16 May 2023
- MIDL 2022
- Readers: Everyone
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling
Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann
- Published: 12 Jan 2021, Last Modified: 12 Oct 2025
- ICLR 2021 Poster
- Readers: Everyone
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness
Raphael Suter, Djordje Miladinovic, Bernhard Schölkopf, Stefan Bauer
- 2019 (modified: 11 Nov 2022)
- ICML 2019
- Readers: Everyone
Granger-Causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks.
Patrick Schwab, Djordje Miladinovic, Walter Karlen
- 2019 (modified: 10 Nov 2022)
- AAAI2019
- Readers: Everyone
Efficient and Flexible Inference for Stochastic Systems
Stefan Bauer, Nico S. Gorbach, Djordje Miladinovic, Joachim M. Buhmann
- 2017 (modified: 11 Nov 2022)
- NIPS 2017
- Readers: Everyone

Đorđe Miladinović

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs

Holistic Modeling in Medical Image Segmentation Using Spatial Recurrence

Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling

Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness

Granger-Causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks.

Efficient and Flexible Inference for Stochastic Systems

Co-Authors