Mitigating algorithmic bias is a critical task in the development and
de...
We tackle the task of synthesizing novel views of an object given a few ...
Generative machine learning models have recently been applied to source ...
What does it mean for a generative AI model to be explainable? The emerg...
Meta-learning algorithms are widely used for few-shot learning. For exam...
Translating source code from one programming language to another is a
cr...
While India remains one of the hotspots of the COVID-19 pandemic, data a...
Generative models have become adept at producing artifacts such as image...
The NLC2CMD Competition hosted at NeurIPS 2020 aimed to bring the power ...
Recently, the automated translation of source code from one programming
...
We formulate a new problem at the intersectionof semi-supervised learnin...
Federated Learning (FL) is an approach to conduct machine learning witho...
This paper reports on the open source project CLAI (Command Line AI), ai...
We consider the problem of aggregating models learned from sequestered,
...
Building multi-domain AI agents is a challenging task and an open proble...
In federated learning problems, data is scattered across different serve...
Machine translation (MT) plays an important role in benefiting linguists...
Knowledge of 3D properties of objects is a necessity in order to build
e...
3D reconstruction from single view images is an ill-posed problem. Infer...