We tackle the problem of neural machine translation of mathematical form...
We present ISAAC (Input-baSed ApproximAte Curvature), a novel method tha...
Contrastive learning has become a prominent ingredient in learning
repre...
Recently, research has increasingly focused on developing efficient neur...
Classic algorithms and machine learning systems like neural networks are...
The top-k classification accuracy is one of the core metrics in machine
...
Many instances of algorithmic bias are caused by distributional shifts. ...
In this work, we present and study a generalized family of differentiabl...
Differentiable sorting algorithms allow training with sorting and rankin...
Post-processing in algorithmic fairness is a versatile approach for
corr...
Reconstructing the 3D geometry of an object from an image is a major
cha...
The integration of algorithmic components into neural architectures has
...
Sorting and ranking supervision is a method for training neural networks...
Artificial neural networks revolutionized many areas of computer science...
We present a novel approach to 3D object reconstruction from its 2D
proj...
While it has become common to perform automated translations on natural
...