Andrea Dittadi

51 papers A* 13A 1Journal 33Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Are Object-Centric Representations Better At Compositional Generalization? CoRR Ferdinand Kapl, Amir Mohammad Karimi-Mamaghan, Maximilian Seitzer, Karl Henrik Johansson, Carsten Marr, Stefan Bauer, Andrea Dittadi
2026	J	`jnl`	Compositional Generalization Requires Linear, Orthogonal Representations in Vision Embedding Models. CoRR Arnas Uselis, Andrea Dittadi, Seong Joon Oh
2026	J	`jnl`	Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics. CoRR Egor Antipov, Alessandro Palma, Lorenzo Consoli, Stephan Günnemann, Andrea Dittadi, Fabian J. Theis
2026	J	`jnl`	From Words to Amino Acids: Does the Curse of Depth Persist? CoRR Aleena Siji, Amir Mohammad Karimi-Mamaghan, Ferdinand Kapl, Tobias Höppe, Emmanouil Angelis, Andrea Dittadi, Maurice Brenner, Michael Heinzinger, Karl Henrik Johansson, Kaitlin Maile, Johannes von Oswald, Stefan Bauer
2026	J	`jnl`	Logit Distance Bounds Representational Similarity. CoRR Beatrix M. G. Nielsen, Emanuele Marconato, Luigi Gresele, Andrea Dittadi, Simon Buchholz
2025	J	`jnl`	Breaking the Likelihood-Quality Trade-off in Diffusion Models by Merging Pretrained Experts. CoRR Yasin Esfandiari, Stefan Bauer, Sebastian U. Stich, Andrea Dittadi
2025	A*	`conf`	Does Data Scaling Lead to Visual Compositional Generalization? ICML Arnas Uselis, Andrea Dittadi, Seong Joon Oh
2025	J	`jnl`	Does Data Scaling Lead to Visual Compositional Generalization? CoRR Arnas Uselis, Andrea Dittadi, Seong Joon Oh
2025	A*	`conf`	Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models. ICLR Amir Mohammad Karimi-Mamaghan, Samuele Papa, Karl Henrik Johansson, Stefan Bauer, Andrea Dittadi
2025	J	`jnl`	Foundations of Diffusion Models in General State Spaces: A Self-Contained Introduction. CoRR Vincent Pauline, Tobias Höppe, Kirill Neklyudov, Alexander Tong, Stefan Bauer, Andrea Dittadi
2025	J	`jnl`	Identifiable Steering via Sparse Autoencoding of Multi-Concept Shifts. CoRR Shruti Joshi, Andrea Dittadi, Sébastien Lachapelle, Dhanya Sridhar
2025	J	`jnl`	Minimum-Excess-Work Guidance. CoRR Christopher Kolloff, Tobias Höppe, Emmanouil Angelis, Mathias Jacob Schreiner, Stefan Bauer, Andrea Dittadi, Simon Olsson
2025	A*	`conf`	Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen. ICLR Alessandro Palma, Till Richter, Hanyi Zhang, Manuel Lubetzki, Alexander Tong, Andrea Dittadi, Fabian J. Theis
2025	J	`jnl`	When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective. CoRR Beatrix M. G. Nielsen, Emanuele Marconato, Andrea Dittadi, Luigi Gresele
2024	A	`conf`	Assessing Neural Network Robustness via Adversarial Pivotal Tuning. WACV Peter Ebert Christensen, Vésteinn Snæbjarnarson, Andrea Dittadi, Serge J. Belongie, Sagie Benaim
2024	A*	`conf`	DiffEnc: Variational Diffusion with a Learned Encoder. ICLR Beatrix Miranda Ginn Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther
2024	J	`jnl`	Diffusion-Based Causal Representation Learning. Entropy Amir Mohammad Karimi-Mamaghan, Andrea Dittadi, Stefan Bauer, Karl Henrik Johansson, Francesco Quinzan
2024	J	`jnl`	Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models. CoRR Amir Mohammad Karimi-Mamaghan, Samuele Papa, Karl Henrik Johansson, Stefan Bauer, Andrea Dittadi
2024	J	`jnl`	Generating Multi-Modal and Multi-Attribute Single-Cell Counts with CFGen. CoRR Alessandro Palma, Till Richter, Hanyi Zhang, Manuel Lubetzki, Alexander Tong, Andrea Dittadi, Fabian J. Theis
2023	A*	`conf`	DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. ICLR Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kügelgen, Armin Kekic, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf
2023	J	`jnl`	DiffEnc: Variational Diffusion with a Learned Encoder. CoRR Beatrix M. G. Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther
2023	J	`jnl`	Diffusion Based Causal Representation Learning. CoRR Amir Mohammad Karimi-Mamaghan, Andrea Dittadi, Stefan Bauer, Karl Henrik Johansson, Francesco Quinzan
2023	J	`jnl`	On the Generalization of Learned Structured Representations. CoRR Andrea Dittadi
2022	A*	`conf`	Assaying Out-Of-Distribution Generalization in Transfer Learning. NeurIPS 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
2022	J	`jnl`	Assaying Out-Of-Distribution Generalization in Transfer Learning. CoRR Florian Wenzel, Andrea Dittadi, Peter Vincent Gehler, Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, Chris Russell, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello
2022	J	`jnl`	Assessing Neural Network Robustness via Adversarial Pivotal Tuning. CoRR Peter Ebert Christensen, Vésteinn Snæbjarnarson, Andrea Dittadi, Serge J. Belongie, Sagie Benaim
2022	J	`jnl`	Conditional Generation of Medical Time Series for Extrapolation to Underrepresented Populations. CoRR Simon Bing, Andrea Dittadi, Stefan Bauer, Patrick Schwab
2022	J	`jnl`	DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. CoRR Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kügelgen, Armin Kekic, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf
2022	J	`jnl`	Diffusion Models for Video Prediction and Infilling. CoRR Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi
2022	J	`jnl`	Diffusion Models for Video Prediction and Infilling. Trans. Mach. Learn. Res. Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi
2022	A*	`conf`	Generalization and Robustness Implications in Object-Centric Learning. ICML Andrea Dittadi, Samuele S. Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
2022	J	`jnl`	Image Super-Resolution With Deep Variational Autoencoders. CoRR Darius Chira, Ilian Haralampiev, Ole Winther, Andrea Dittadi, Valentin Liévin
2022	—	`conf`	Image Super-Resolution with Deep Variational Autoencoders. ECCV Workshops (2) Darius Chira, Ilian Haralampiev, Ole Winther, Andrea Dittadi, Valentin Liévin
2022	J	`jnl`	Inductive Biases for Object-Centric Representations in the Presence of Complex Textures. CoRR Samuele Papa, Ole Winther, Andrea Dittadi
2022	A*	`conf`	The Role of Pretrained Representations for the OOD Generalization of RL Agents. ICLR Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
2021	J	`jnl`	Boxhead: A Dataset for Learning Hierarchical Representations. CoRR Yukun Chen, Frederik Träuble, Andrea Dittadi, Stefan Bauer, Bernhard Schölkopf
2021	A*	`conf`	Full-Body Motion from a Single Head-Mounted Device: Generating SMPL Poses from Partial Observations. ICCV Andrea Dittadi, Sebastian Dziadzio, Darren Cosker, Ben Lundell, Thomas J. Cashman, Jamie Shotton
2021	J	`jnl`	Generalization and Robustness Implications in Object-Centric Learning. CoRR Andrea Dittadi, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
2021	A*	`conf`	On Disentangled Representations Learned from Correlated Data. ICML Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
2021	A*	`conf`	On the Transfer of Disentangled Representations in Realistic Settings. ICLR Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf
2021	A*	`conf`	Planning from Pixels in Atari with Learned Symbolic Representations. AAAI Andrea Dittadi, Frederik K. Drachmann, Thomas Bolander
2021	J	`jnl`	Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. CoRR Andrea Dittadi, Frederik Träuble, Manuel Wüthrich, Felix Widmaier, Peter V. Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
2020	J	`jnl`	On the Transfer of Disentangled Representations in Realistic Settings. CoRR Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf
2020	J	`jnl`	Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds. CoRR Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther
2020	A*	`conf`	Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds. NeurIPS Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther
2020	J	`jnl`	Planning From Pixels in Atari With Learned Symbolic Representations. CoRR Andrea Dittadi, Frederik K. Drachmann, Thomas Bolander
2019	J	`jnl`	LAVAE: Disentangling Location and Appearance. CoRR Andrea Dittadi, Ole Winther
2019	J	`jnl`	Semi-Supervised Variational Autoencoder for Survival Prediction. CoRR Sveinn Pálsson, Stefano Cerri, Andrea Dittadi, Koen Van Leemput
2019	—	`conf`	Semi-supervised Variational Autoencoder for Survival Prediction. BrainLes@MICCAI (2) Sveinn Pálsson, Stefano Cerri, Andrea Dittadi, Koen Van Leemput
2018	—	`conf`	Learning to Plan from Raw Data in Grid-based Games. GCAI Andrea Dittadi, Thomas Bolander, Ole Winther
2016	—	`conf`	Spreading and repetitions in satellite MAC protocols. ICC Alessandro Biason, Andrea Dittadi, Michele Zorzi