Controllable text generation concerns two fundamental tasks of wide applications, namely
generating text of given attributes (ie, attribute-conditional generation), and minimally editing …

This paper proposes a Disentangled gEnerative cAusal Representation (DEAR) learning
method under appropriate supervised information. Unlike existing disentanglement methods …

Abstract Controllable Image Synthesis (CIS) is a methodology that allows users to generate
desired images or manipulate specific attributes of images by providing precise input …

We consider the problem of answering observational, interventional, and counterfactual
queries in a causally sufficient setting where only observational data and the causal graph …

This paper proposes a Disentangled gEnerative cAusal Representation (DEAR) learning
method. Unlike existing disentanglement methods that enforce independence of the latent …

In this paper, we introduce VACA, a novel class of variational graph autoencoders for causal
inference in the absence of hidden confounders, when only observational data and the …

Cognitive diagnosis is vital for intelligent education to determine students' knowledge
mastery levels from their response logs. The Q-matrix, representing the relationships …

In this paper, we introduce VACA, a novel class of variational graph autoencoders for causal
inference in the absence of hidden confounders, when only observational data and the …

Controllable image synthesis is a method by which users can manipulate a particular
attribute in an image in a semantically meaningful way without affecting other attributes. This …

In the age of artificial intelligence, Machine Learning (ML) has become a pervasive force,
impacting countless aspects of our lives. As ML's influence expands, concerns about its …