Publications

Image Super-Resolution Using Deep Convolutional Networks

We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is...

Communication Theory of Secrecy Systems*

THE problems of cryptography and secrecy systems furnish an interesting application of communication theory. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="htt...

Fast, sensitive and accurate integration of single-cell data with Harmony

<scp>UCSF ChimeraX</scp>: Structure visualization for researchers, educators, and developers

Abstract UCSF ChimeraX is the next‐generation interactive visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera...

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e.g., 10-150...

Multivariate Adaptive Regression Splines

A new method is presented for flexible regression modeling of high dimensional data. The model takes the form of an expansion in product spline basis functions, where the number...

Path Aggregation Network for Instance Segmentation

The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in ...

Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories

International audience

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

A Comprehensive Survey on Graph Neural Networks

Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language u...

Genome sequencing in microfabricated high-density picolitre reactors

The proliferation of large-scale DNA-sequencing projects in recent years has driven a search for alternative methods to reduce time and cost. Here we describe a scalable, highly...

EfficientDet: Scalable and Efficient Object Detection

Model efficiency has become increasingly important in computer vision. In this paper, we systematically study neural network architecture design choices for object detection and...