In this paper we examine the ability to perform causal reasoning with equilibrium models. We explicate a postulate, which we term the Manipulation Postulate, that is required in o...
Identifiability becomes an essential requirement for learning machines when the models contain physically interpretable parameters. This paper presents two approaches to examining...
This paper addresses the inference of probabilistic classification models using weakly supervised learning. In contrast to previous work, the use of proportion-based training data...
Carla Scalarin, Jacques Masse, Jean-Marc Boucher, ...
Effective problem-solving about complex engineered devices requires device models that are both adequate for the problem and computationally efficient . Producing such models requ...
P. Pandurang Nayak, Leo Joskowicz, Sanjaya Addanki
In software protection we typically have to deal with the white-box attack model. In this model an attacker is assumed to have full access to the software and full control over it...