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To date, there has been no formal study of the statistical cost of interpretability in machine learning. As such, the discourse around …
Language User Interfaces (LUIs) could improve human-machine interaction for a wide variety of tasks, such as playing music, getting …
Generative deep learning has sparked a new wave of Super-Resolution (SR) algorithms that enhance single images with impressive …
From an environmental standpoint, there are a few crucial aspects of training a neural network that have a major impact on the quantity …
Computing optimal transport maps between high-dimensional and continuous distributions is a challenging problem in optimal transport …
While progress has been made in crafting visually imperceptible adversarial examples, constructing semantically meaningful ones remains …
Pruning is a well-established technique for removing unnecessary structure from neural networks after training to improve the …
We present Hinted Networks: a collection of architectural transformations for improving the accuracies of neural network models for …
This article proposes Adversarially-Trained Normalized Noisy-Feature Auto-Encoder (ATNNFAE) for byte-level text generation. An ATNNFAE …
It has been postulated that a good representation is one that disentangles the underlying explanatory factors of variation. However, it …