DOI,IST REx ID,Research Group,Title of publication
null,14177,FrLo,On disentangled representations learned from correlated data
null,14178,FrLo,On the transfer of disentangled representations in realistic settings
null,14179,FrLo,Self-supervised learning with data augmentations provably isolates content from style
null,14180,FrLo,Dynamic inference with neural interpreters
10.24963/ijcai.2021/322,14181,FrLo,Boosting variational inference with locally adaptive step-sizes
null,14182,FrLo,Backward-compatible prediction updates: A probabilistic approach
10.48550/arXiv.2111.13693,14221,FrLo,Enforcing and discovering structure in machine learning
null,14332,FrLo,Representation learning for out-of-distribution generalization in reinforcement learning
10.1093/bioinformatics/btaa843,14125,FrLo,SCIM: Universal single-cell matching with unpaired feature sets
10.1609/aaai.v34i09.7120,14186,FrLo,A commentary on the unsupervised learning of disentangled representations
null,14187,FrLo,Stochastic Frank-Wolfe for constrained finite-sum minimization
null,14188,FrLo,Weakly-supervised disentanglement without compromises
null,14195,FrLo,A sober look at the unsupervised learning of disentangled representations and their evaluation
null,14326,FrLo,Object-centric learning with slot attention
null,14184,FrLo,Disentangling factors of variation using few labels
null,14189,FrLo,The incomplete Rosetta Stone problem: Identifiability results for multi-view nonlinear ICA
null,14190,FrLo,On the transfer of inductive bias from simulation to the real world: a new disentanglement dataset
null,14191,FrLo,Stochastic Frank-Wolfe for composite convex minimization
null,14193,FrLo,Are disentangled representations helpful for abstract visual reasoning?
null,14197,FrLo,On the fairness of disentangled representations