DOI,IST REx ID,Research Group,Title of publication
null,14219,FrLo,Unsupervised semantic segmentation with self-supervised object-centric representations
null,14222,FrLo,Unsupervised object learning via common fate
10.48550/arXiv.2307.09552,14333,FrLo,Self-compatibility: Evaluating causal discovery without ground truth
null,14949,FrLo,Image retrieval outperforms diffusion models on data augmentation
null,14958,FrLo,A sparsity principle for partially observable causal representation learning
10.48550/arXiv.2310.14246,14961,FrLo,Shortcuts for causal discovery of nonlinear models by score matching
10.48550/arXiv.2309.09858,14962,FrLo,Unsupervised open-vocabulary object localization in videos
10.48550/arXiv.2309.00233,14963,FrLo,Object-centric multiple object tracking
null,14965,FrLo,Methods of determining correspondences between biological properties of cells
null,14974,FrLo,Causality in the time of LLMs: Round table discussion results of CLeaR 2023
null,14210,FrLo,Leveraging sparse and shared feature activations for disentangled representation learning
10.52202/075280-2418,14952,FrLo,Latent space translation via semantic alignment
null,14207,FrLo,Rotating features for object discovery
null,14948,FrLo,Grounded object centric learning
10.52202/075280-2050,14954,FrLo,Assumption violations in causal discovery and the robustness of score matching
10.52202/075280-0147,14953,FrLo,Sample complexity bounds for score-matching: Causal discovery and generative modeling
null,14093,FrLo, Faster one-sample stochastic conditional gradient method for composite convex minimization
null,14106,FrLo,Are two heads the same as one? Identifying disparate treatment in fair neural networks
10.48550/arXiv.2210.12733,14107,FrLo,Self-supervised amodal video object segmentation
10.1109/cvpr52688.2022.01016,14114,FrLo,Leveling down in computer vision: Pareto inefficiencies in fair deep classifiers