_id,title
14200,Challenging common assumptions in the unsupervised learning of disentangled representations
14327,Competitive training of mixtures of independent deep generative models
14198,SOM-VAE: Interpretable discrete representation learning on time series
14201,Boosting variational inference: An optimization perspective
14202,Boosting black box variational inference
14203,A conditional gradient framework for composite convex minimization with applications to semidefinite programming
14204,On matching pursuit and coordinate descent
14224,Clustering meets implicit generative models
14205,A unified optimization view on generalized matching pursuit and Frank-Wolfe
14206,Greedy algorithms for cone constrained optimization with convergence guarantees