De novo therapeutic design is challenged by a vast chemical repertoire a...
We propose the Sobolev Independence Criterion (SIC), an interpretable
de...
We introduce Multi-Frame Cross-Entropy training (MFCE) for convolutional...
In this paper we propose to perform model ensembling in a multiclass or ...
Given the emerging global threat of antimicrobial resistance, new method...
In this paper, we propose a novel Convolutional Neural Network (CNN)
arc...
We introduce Regularized Kernel and Neural Sobolev Descent for transport...
In this paper we propose a new conditional GAN for image captioning that...
We present an empirical investigation of a recent class of Generative
Ad...
We propose a new Integral Probability Metric (IPM) between distributions...
Generative Adversarial Networks (GANs) are powerful models for learning
...
One of the most difficult speech recognition tasks is accurate recogniti...
We introduce new families of Integral Probability Metrics (IPM) for trai...
In computer vision pixelwise dense prediction is the task of predicting ...
We describe a collection of acoustic and language modeling techniques th...
Very deep CNNs with small 3x3 kernels have recently been shown to achiev...
Convolutional neural networks (CNNs) are a standard component of many cu...