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Andrea Dittadi
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2020 – today
- 2024
- [j2]Amir Mohammad Karimi-Mamaghan, Andrea Dittadi, Stefan Bauer, Karl Henrik Johansson, Francesco Quinzan:
Diffusion-Based Causal Representation Learning. Entropy 26(7): 556 (2024) - [c15]Beatrix Miranda Ginn Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther:
DiffEnc: Variational Diffusion with a Learned Encoder. ICLR 2024 - [c14]Peter Ebert Christensen, Vésteinn Snæbjarnarson, Andrea Dittadi, Serge J. Belongie, Sagie Benaim:
Assessing Neural Network Robustness via Adversarial Pivotal Tuning. WACV 2024: 2940-2949 - [i20]Alessandro Palma, Till Richter, Hanyi Zhang, Manuel Lubetzki, Alexander Tong, Andrea Dittadi, Fabian J. Theis:
Generating Multi-Modal and Multi-Attribute Single-Cell Counts with CFGen. CoRR abs/2407.11734 (2024) - [i19]Amir Mohammad Karimi-Mamaghan, Samuele Papa, Karl Henrik Johansson, Stefan Bauer, Andrea Dittadi:
Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models. CoRR abs/2407.15589 (2024) - 2023
- [c13]Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kügelgen, Armin Kekic, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf:
DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. ICLR 2023 - [i18]Andrea Dittadi:
On the Generalization of Learned Structured Representations. CoRR abs/2304.13001 (2023) - [i17]Beatrix M. G. Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther:
DiffEnc: Variational Diffusion with a Learned Encoder. CoRR abs/2310.19789 (2023) - [i16]Amir Mohammad Karimi-Mamaghan, Andrea Dittadi, Stefan Bauer, Karl Henrik Johansson, Francesco Quinzan:
Diffusion Based Causal Representation Learning. CoRR abs/2311.05421 (2023) - 2022
- [j1]Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi:
Diffusion Models for Video Prediction and Infilling. Trans. Mach. Learn. Res. 2022 (2022) - [c12]Darius Chira, Ilian Haralampiev, Ole Winther, Andrea Dittadi, Valentin Liévin:
Image Super-Resolution with Deep Variational Autoencoders. ECCV Workshops (2) 2022: 395-411 - [c11]Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer:
The Role of Pretrained Representations for the OOD Generalization of RL Agents. ICLR 2022 - [c10]Andrea Dittadi, Samuele S. Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello:
Generalization and Robustness Implications in Object-Centric Learning. ICML 2022: 5221-5285 - [c9]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:
Assaying Out-Of-Distribution Generalization in Transfer Learning. NeurIPS 2022 - [i15]Simon Bing, Andrea Dittadi, Stefan Bauer, Patrick Schwab:
Conditional Generation of Medical Time Series for Extrapolation to Underrepresented Populations. CoRR abs/2201.08186 (2022) - [i14]Darius Chira, Ilian Haralampiev, Ole Winther, Andrea Dittadi, Valentin Liévin:
Image Super-Resolution With Deep Variational Autoencoders. CoRR abs/2203.09445 (2022) - [i13]Samuele Papa, Ole Winther, Andrea Dittadi:
Inductive Biases for Object-Centric Representations in the Presence of Complex Textures. CoRR abs/2204.08479 (2022) - [i12]Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi:
Diffusion Models for Video Prediction and Infilling. CoRR abs/2206.07696 (2022) - [i11]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:
Assaying Out-Of-Distribution Generalization in Transfer Learning. CoRR abs/2207.09239 (2022) - [i10]Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kügelgen, Armin Kekic, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf:
DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. CoRR abs/2210.00364 (2022) - [i9]Peter Ebert Christensen, Vésteinn Snæbjarnarson, Andrea Dittadi, Serge J. Belongie, Sagie Benaim:
Assessing Neural Network Robustness via Adversarial Pivotal Tuning. CoRR abs/2211.09782 (2022) - 2021
- [c8]Andrea Dittadi, Frederik K. Drachmann, Thomas Bolander:
Planning from Pixels in Atari with Learned Symbolic Representations. AAAI 2021: 4941-4949 - [c7]Andrea Dittadi, Sebastian Dziadzio, Darren Cosker, Ben Lundell, Thomas J. Cashman, Jamie Shotton:
Full-Body Motion from a Single Head-Mounted Device: Generating SMPL Poses from Partial Observations. ICCV 2021: 11667-11677 - [c6]Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf:
On the Transfer of Disentangled Representations in Realistic Settings. ICLR 2021 - [c5]Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer:
On Disentangled Representations Learned from Correlated Data. ICML 2021: 10401-10412 - [i8]Andrea Dittadi, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello:
Generalization and Robustness Implications in Object-Centric Learning. CoRR abs/2107.00637 (2021) - [i7]Andrea Dittadi, Frederik Träuble, Manuel Wüthrich, Felix Widmaier, Peter V. Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer:
Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. CoRR abs/2107.05686 (2021) - [i6]Yukun Chen, Frederik Träuble, Andrea Dittadi, Stefan Bauer, Bernhard Schölkopf:
Boxhead: A Dataset for Learning Hierarchical Representations. CoRR abs/2110.03628 (2021) - 2020
- [c4]Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther:
Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds. NeurIPS 2020 - [i5]Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther:
Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds. CoRR abs/2008.01998 (2020) - [i4]Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf:
On the Transfer of Disentangled Representations in Realistic Settings. CoRR abs/2010.14407 (2020) - [i3]Andrea Dittadi, Frederik K. Drachmann, Thomas Bolander:
Planning From Pixels in Atari With Learned Symbolic Representations. CoRR abs/2012.09126 (2020)
2010 – 2019
- 2019
- [c3]Sveinn Pálsson, Stefano Cerri, Andrea Dittadi, Koen Van Leemput:
Semi-supervised Variational Autoencoder for Survival Prediction. BrainLes@MICCAI (2) 2019: 124-134 - [i2]Andrea Dittadi, Ole Winther:
LAVAE: Disentangling Location and Appearance. CoRR abs/1909.11813 (2019) - [i1]Sveinn Pálsson, Stefano Cerri, Andrea Dittadi, Koen Van Leemput:
Semi-Supervised Variational Autoencoder for Survival Prediction. CoRR abs/1910.04488 (2019) - 2018
- [c2]Andrea Dittadi, Thomas Bolander, Ole Winther:
Learning to Plan from Raw Data in Grid-based Games. GCAI 2018: 54-67 - 2016
- [c1]Alessandro Biason, Andrea Dittadi, Michele Zorzi:
Spreading and repetitions in satellite MAC protocols. ICC 2016: 1-6
Coauthor Index
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last updated on 2024-10-07 22:18 CEST by the dblp team
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