In this work, we introduce a hybrid neural-guided/genetic programming approach tosymbolic regression andothercombinatorial optimization problems.

The total loss of the model is a combination of both regularization terms and a reconstructionloss. Herexr refers to reference image,xa to adversarial image and xr, xa to their corresponding reconstructions. The maximum input noise perturbation levelλ is limited to1,3 and 5. However, it should be also noted that with PGD-based training, the computational time is two times more expensive than our original method. These attacks are more successful when the adversarial reconstructions are less similar in appearance to the clean reconstructions.

Neolithic period to the Industrial Revolution and includes information reviewed and assembled by history experts and graduate research assistants.

We follow [8] to train the depth estimation model and compute thedepth estimation error onpixelsassociated with ground truth LiDARpoints.

The blue 3D points are obtained usingPSMNet[4].

Constructive solid geometry (CSG) is a classical CAD representation; it models a 3D shape as a recursive assembly of solid primitives, e.g., cuboids, cylinders, etc., through Boolean operations