
-
Self-supervised Dynamic CT Perfusion Image Denoising with Deep Neural Networks
Dynamic computed tomography perfusion (CTP) imaging is a promising appro...
read it
-
Cascaded Text Generation with Markov Transformers
The two dominant approaches to neural text generation are fully autoregr...
read it
-
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos
Learning to predict scene depth from RGB inputs is a challenging task bo...
read it
-
Deep learning tools for the measurement of animal behavior in neuroscience
Recent advances in computer vision have made accurate, fast and robust m...
read it
-
Unsupervised Discovery of Sparse Multimodal Representations in High Dimensional Data
Extracting an understanding of the underlying system from high dimension...
read it
-
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models
AI Safety is a major concern in many deep learning applications such as ...
read it
-
Designing Environments Conducive to Interpretable Robot Behavior
Designing robots capable of generating interpretable behavior is a prere...
read it
-
Towards generative adversarial networks as a new paradigm for radiology education
Medical students and radiology trainees typically view thousands of imag...
read it
-
Subgraph Neural Networks
Deep learning methods for graphs achieve remarkable performance on many ...
read it
-
Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images
The rapidly emerging field of computational pathology has the potential ...
read it
-
Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting
Unsupervised domain adaptation (UDA) for nuclei instance segmentation is...
read it
-
Learning to Complement Humans
A rising vision for AI in the open world centers on the development of s...
read it
-
Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis
Cancer diagnosis, prognosis and therapeutic response predictions are bas...
read it
-
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation
Fully convolutional neural networks (FCNs), and in particular U-Nets, ha...
read it
-
Neuroscience-inspired online unsupervised learning algorithms
Although the currently popular deep learning networks achieve unpreceden...
read it
-
Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks
Solutions to differential equations are of significant scientific and en...
read it
-
A Topological Nomenclature for 3D Shape Analysis in Connectomics
An essential task in nano-scale connectomics is the morphology analysis ...
read it
-
Emergent Properties of Foveated Perceptual Systems
We introduce foveated perceptual systems, inspired by human biological s...
read it
-
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images
Supervised deep learning algorithms have enabled significant performance...
read it
-
Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging
Fetal magnetic resonance imaging (MRI) is challenged by uncontrollable, ...
read it
-
Deep Double Descent: Where Bigger Models and More Data Hurt
We show that a variety of modern deep learning tasks exhibit a "double-d...
read it
-
Learning to Prune: Speeding up Repeated Computations
It is common to encounter situations where one must solve a sequence of ...
read it
-
A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI
Fetal cortical plate segmentation is essential in quantitative analysis ...
read it
-
Too many cooks: Coordinating multi-agent collaboration through inverse planning
Collaboration requires agents to coordinate their behavior on the fly, s...
read it
-
Collapsing Bandits and Their Application to Public Health Interventions
We propose and study Collpasing Bandits, a new restless multi-armed band...
read it
-
Computationally Efficient Cascaded Training for Deep Unrolled Network in CT Imaging
Dose reduction in computed tomography (CT) has been of great research in...
read it
-
Thwarting Adversarial Examples: An L_0-RobustSparse Fourier Transform
We give a new algorithm for approximating the Discrete Fourier transform...
read it
-
A machine learning-based method for estimating the number and orientations of major fascicles in diffusion-weighted magnetic resonance imaging
Multi-compartment modeling of diffusion-weighted magnetic resonance imag...
read it
-
Fast, Structured Clinical Documentation via Contextual Autocomplete
We present a system that uses a learned autocompletion mechanism to faci...
read it
-
Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?
Commercial iterative reconstruction techniques on modern CT scanners tar...
read it
-
Seeing in the dark with recurrent convolutional neural networks
Classical convolutional neural networks (cCNNs) are very good at categor...
read it
-
Multi-Task Ordinal Regression for Jointly Predicting the Trustworthiness and the Leading Political Ideology of News Media
In the context of fake news, bias, and propaganda, we study two importan...
read it
-
ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries
In this work we introduce ExpertMatcher, a method for automating deep le...
read it
-
A Learning Strategy for Contrast-agnostic MRI Segmentation
We present a deep learning strategy that enables, for the first time, co...
read it
-
Online Residential Demand Response via Contextual Multi-Armed Bandits
Residential load demands have huge potential to be exploited to enhance ...
read it
-
Bandit-PAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits
Clustering is a ubiquitous task in data science. Compared to the commonl...
read it
-
Fast Physical Activity Suggestions: Efficient Hyperparameter Learning in Mobile Health
Users can be supported to adopt healthy behaviors, such as regular physi...
read it
-
Smarter Parking: Using AI to Identify Parking Inefficiencies in Vancouver
On-street parking is convenient, but has many disadvantages: on-street s...
read it
-
Assessing the validity of saliency maps for abnormality localization in medical imaging
Saliency maps have become a widely used method to assess which areas of ...
read it
-
Super-BPD: Super Boundary-to-Pixel Direction for Fast Image Segmentation
Image segmentation is a fundamental vision task and a crucial step for m...
read it
-
Self-Organization and Artificial Life
Self-organization can be broadly defined as the ability of a system to d...
read it
-
Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures
Generative models have achieved impressive results in many domains inclu...
read it
-
Generative-based Airway and Vessel Morphology Quantification on Chest CT Images
Accurately and precisely characterizing the morphology of small pulmonar...
read it
-
A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models
We present a timely and novel methodology that combines disease estimate...
read it
-
A Large Dataset of Historical Japanese Documents with Complex Layouts
Deep learning-based approaches for automatic document layout analysis an...
read it
-
CheckNet: Secure Inference on Untrusted Devices
We introduce CheckNet, a method for secure inference with deep neural ne...
read it
-
Generalized Principal Component Analysis
Generalized principal component analysis (GLM-PCA) facilitates dimension...
read it
-
High Accuracy Tumor Diagnoses and Benchmarking of Hematoxylin and Eosin Stained Prostate Core Biopsy Images Generated by Explainable Deep Neural Networks
Histopathological diagnoses of tumors in tissue biopsy after Hematoxylin...
read it
-
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
This paper studies learning the representations of whole graphs in both ...
read it
-
Exploiting Parallelism Opportunities with Deep Learning Frameworks
State-of-the-art machine learning frameworks support a wide variety of d...
read it