Dittadi, Andrea

26 publications

ICLRW 2025 Beyond Decodability: Linear Feature Spaces Enable Visual Compositional Generalization Arnas Uselis, Andrea Dittadi, Seong Joon Oh

ICLRW 2025 Breaking the Likelihood--Quality Trade-Off in Diffusion Models by Merging Pretrained Experts Yasin Esfandiari, Stefan Bauer, Sebastian U Stich, Andrea Dittadi

ICML 2025 Does Data Scaling Lead to Visual Compositional Generalization? Arnas Uselis, Andrea Dittadi, Seong Joon Oh

ICLR 2025 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, Andrea Dittadi, Fabian J Theis

ICLRW 2025 Object-Centric Representations Generalize Better Compositionally with Less Compute Ferdinand Kapl, Amir Mohammad Karimi Mamaghan, Max Horn, Carsten Marr, Stefan Bauer, Andrea Dittadi

NeurIPS 2025 When Does Closeness in Distribution Imply Representational Similarity? an Identifiability Perspective Beatrix Miranda Ginn Nielsen, Emanuele Marconato, Andrea Dittadi, Luigi Gresele

WACV 2024 Assessing Neural Network Robustness via Adversarial Pivotal Tuning Peter Ebert Christensen, Vésteinn Snæbjarnarson, Andrea Dittadi, Serge Belongie, Sagie Benaim

NeurIPSW 2024 Challenges in Explaining Representational Similarity Through Identifiability Beatrix Miranda Ginn Nielsen, Luigi Gresele, Andrea Dittadi

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

ICLRW 2024 cellFlow: A Generative Flow-Based Model for Single-Cell Count Data Alessandro Palma, Till Richter, Hanyi Zhang, Andrea Dittadi, Fabian J Theis

ICLR 2023 DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability Cian Eastwood, Andrei Liviu Nicolicioiu, Julius Von Kügelgen, Armin Kekić, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf

ICMLW 2023 Diffusion Based Causal Representation Learning Amir Mohammad Karimi Mamaghan, Andrea Dittadi, Stefan Bauer, Francesco Quinzan

NeurIPS 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, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello

TMLR 2022 Diffusion Models for Video Prediction and Infilling Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi

NeurIPSW 2022 Diffusion Models for Video Prediction and Infilling Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi

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

ECCVW 2022 Image Super-Resolution with Deep Variational Autoencoders Darius Chira, Ilian Haralampiev, Ole Winther, Andrea Dittadi, Valentin Liévin

ICLR 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

NeurIPSW 2021 Boxhead: A Dataset for Learning Hierarchical Representations Yukun Chen, Andrea Dittadi, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf

ICCV 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, Jamie Shotton

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

ICLR 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

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

ICMLW 2021 Representation Learning for Out-of-Distribution Generalization in Reinforcement Learning Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer

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