Abstract: In implementations of systems for estimating effects with latent representations, a computing device implements an estimation system to receive input data via a network describing interactions of client devices included in a group of client devices. The estimation system generates a first latent vector representation of a first segment of the client devices and a second latent vector representation of a second segment of the client devices using an encoder of a machine learning model. A change vector is computed based on a difference between the first latent vector representation and the second latent vector representation in a latent space of the machine learning model. The estimation system generates an indication of an effect of a treatment on a third segment of the client devices based on the change vector using a decoder of the machine learning model.

Abstract: According to the present disclosure, the present invention discloses a methodology wherein the integrated circuit (IC) design process is independent of a pre-existing standard cell library with fixed or static driving strengths. The present invention utilizes a completely automated process for IC design utilizing a neural network based configurable cell library which generates design specific standard cells with desired driving strengths on the run. The driving strengths of the design specific standard cells are determined based on the constraints of the target IC design.

Abstract: The present invention relates to pharmaceutical compositions of sodium picosulfate, magnesium oxide and citric acid. In particular, the invention relates to pharmaceutical compositions comprise granules having a layer of sodium picosulfate on neutral carrier/s. The invention also relates to processes for the preparation of such compositions and use thereof for bowel cleansing.