Spreading and repetitions in satellite MAC protocols. - Alessandro Biason; Andrea Dittadi; Michele Zorzi (ICC, 2016)

Learning to Plan from Raw Data in Grid-based Games. - Andrea Dittadi; Thomas Bolander; Ole Winther (GCAI, 2018)

Semi-supervised Variational Autoencoder for Survival Prediction. - Sveinn Pálsson; Stefano Cerri; Andrea Dittadi; Koen Van Leemput (BrainLes@MICCAI (2), 2019)

LAVAE: Disentangling Location and Appearance. - Andrea Dittadi; Ole Winther (CoRR, 2019)

Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds. - Valentin Liévin; Andrea Dittadi; Anders Christensen; Ole Winther (NeurIPS, 2020)

Planning from Pixels in Atari with Learned Symbolic Representations. - Andrea Dittadi; Frederik K. Drachmann; Thomas Bolander (AAAI, 2021)

Full-Body Motion from a Single Head-Mounted Device: Generating SMPL Poses from Partial Observations. - Andrea Dittadi; Sebastian Dziadzio; Darren Cosker; Ben Lundell; Thomas J. Cashman 001; Jamie Shotton (ICCV, 2021)

On the Transfer of Disentangled Representations in Realistic Settings. - Andrea Dittadi; Frederik Träuble; Francesco Locatello; Manuel Wuthrich; Vaibhav Agrawal; Ole Winther; Stefan Bauer; Bernhard Schölkopf (ICLR, 2021)

On Disentangled Representations Learned from Correlated Data. - Frederik Träuble; Elliot Creager; Niki Kilbertus; Francesco Locatello; Andrea Dittadi; Anirudh Goyal; Bernhard Schölkopf; Stefan Bauer (ICML, 2021)

Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. - Andrea Dittadi; Frederik Träuble; Manuel Wüthrich; Felix Widmaier; Peter V. Gehler; Ole Winther; Francesco Locatello; Olivier Bachem; Bernhard Schölkopf; Stefan Bauer (CoRR, 2021)

Boxhead: A Dataset for Learning Hierarchical Representations. - Yukun Chen; Frederik Träuble; Andrea Dittadi; Stefan Bauer; Bernhard Schölkopf (CoRR, 2021)

Image Super-Resolution with Deep Variational Autoencoders. - Darius Chira; Ilian Haralampiev; Ole Winther; Andrea Dittadi; Valentin Liévin (ECCV Workshops (2), 2022)

The Role of Pretrained Representations for the OOD Generalization of RL Agents. - Frederik Träuble; Andrea Dittadi; Manuel Wuthrich; Felix Widmaier; Peter Vincent Gehler; Ole Winther; Francesco Locatello; Olivier Bachem; Bernhard Schölkopf; Stefan Bauer (ICLR, 2022)

Generalization and Robustness Implications in Object-Centric Learning. - Andrea Dittadi; Samuele S. Papa; Michele De Vita; Bernhard Schölkopf; Ole Winther; Francesco Locatello (ICML, 2022)

Assaying Out-Of-Distribution Generalization in Transfer Learning. - Florian Wenzel; Andrea Dittadi; Peter V. Gehler; Carl-Johann Simon-Gabriel; Max Horn; Dominik Zietlow; David Kernert; Chris Russell 001; Thomas Brox; Bernt Schiele; Bernhard Schölkopf; Francesco Locatello (NeurIPS, 2022)

Conditional Generation of Medical Time Series for Extrapolation to Underrepresented Populations. - Simon Bing; Andrea Dittadi; Stefan Bauer; Patrick Schwab (CoRR, 2022)

Inductive Biases for Object-Centric Representations in the Presence of Complex Textures. - Samuele Papa; Ole Winther; Andrea Dittadi (CoRR, 2022)

Diffusion Models for Video Prediction and Infilling. - Tobias Höppe; Arash Mehrjou; Stefan Bauer; Didrik Nielsen; Andrea Dittadi (Trans. Mach. Learn. Res., 2022)

DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. - Cian Eastwood; Andrei Liviu Nicolicioiu; Julius von Kügelgen; Armin Kekic; Frederik Träuble; Andrea Dittadi; Bernhard Schölkopf (ICLR, 2023)

On the Generalization of Learned Structured Representations. - Andrea Dittadi (CoRR, 2023)

DiffEnc: Variational Diffusion with a Learned Encoder. - Beatrix Miranda Ginn Nielsen; Anders Christensen; Andrea Dittadi; Ole Winther (ICLR, 2024)

Assessing Neural Network Robustness via Adversarial Pivotal Tuning. - Peter Ebert Christensen; Vésteinn Snæbjarnarson; Andrea Dittadi; Serge J. Belongie; Sagie Benaim (WACV, 2024)

Generating Multi-Modal and Multi-Attribute Single-Cell Counts with CFGen. - Alessandro Palma; Till Richter; Hanyi Zhang; Manuel Lubetzki; Alexander Tong 001; Andrea Dittadi; Fabian J. Theis (CoRR, 2024)

Diffusion-Based Causal Representation Learning. - Amir Mohammad Karimi-Mamaghan; Andrea Dittadi; Stefan Bauer; Karl Henrik Johansson; Francesco Quinzan (Entropy, 2024)

Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models. - Amir Mohammad Karimi-Mamaghan; Samuele Papa; Karl Henrik Johansson; Stefan Bauer; Andrea Dittadi (ICLR, 2025)

Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen. - Alessandro Palma; Till Richter; Hanyi Zhang; Manuel Lubetzki; Alexander Tong 001; Andrea Dittadi; Fabian J. Theis (ICLR, 2025)

Identifiable Steering via Sparse Autoencoding of Multi-Concept Shifts. - Shruti Joshi; Andrea Dittadi; Sébastien Lachapelle; Dhanya Sridhar (CoRR, 2025)

Minimum-Excess-Work Guidance. - Christopher Kolloff; Tobias Höppe; Emmanouil Angelis; Mathias Jacob Schreiner; Stefan Bauer; Andrea Dittadi; Simon Olsson (CoRR, 2025)

When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective. - Beatrix M. G. Nielsen; Emanuele Marconato; Andrea Dittadi; Luigi Gresele (CoRR, 2025)

Does Data Scaling Lead to Visual Compositional Generalization? - Arnas Uselis; Andrea Dittadi; Seong Joon Oh (CoRR, 2025)