Harvard University

∙ Cambridge , United States ∙ 0 followers

Harvard University is a private Ivy League research university in Cambridge, Massachusetts, with about 6,700 undergraduate students and about 15,250 postgraduate students.

Featured Researchers

Yang Liu
291 publications
Rui Wang
131 publications
Hao Wang
121 publications
Xiang Li
70 publications
Finale Doshi-Velez
61 publications
Fan Zhang
61 publications
José Miguel Hernández-Lobato
58 publications
Xin Chen
54 publications
James Zou
49 publications
Alexander M. Rush
48 publications
Ryan P. Adams
47 publications

Self-supervised Dynamic CT Perfusion Image Denoising with Deep Neural Networks

Dynamic computed tomography perfusion (CTP) imaging is a promising appro...
05/19/2020 ∙ by Dufan Wu, et al. ∙ 34 ∙ share

read it
Cascaded Text Generation with Markov Transformers

The two dominant approaches to neural text generation are fully autoregr...
06/01/2020 ∙ by Yuntian Deng, et al. ∙ 31 ∙ share

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...
11/15/2018 ∙ by Vincent Casser, et al. ∙ 30 ∙ share

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...
09/30/2019 ∙ by Mackenzie W. Mathis, et al. ∙ 27 ∙ share

read it
Unsupervised Discovery of Sparse Multimodal Representations in High Dimensional Data

Extracting an understanding of the underlying system from high dimension...
10/13/2019 ∙ by Samuel Melton, et al. ∙ 26 ∙ share

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 ...
11/18/2019 ∙ by Tong Che, et al. ∙ 26 ∙ share

read it
Designing Environments Conducive to Interpretable Robot Behavior

Designing robots capable of generating interpretable behavior is a prere...
07/02/2020 ∙ by Anagha Kulkarni, et al. ∙ 21 ∙ share

read it
Towards generative adversarial networks as a new paradigm for radiology education

Medical students and radiology trainees typically view thousands of imag...
12/04/2018 ∙ by Samuel G. Finlayson, et al. ∙ 20 ∙ share

read it
Subgraph Neural Networks

Deep learning methods for graphs achieve remarkable performance on many ...
06/18/2020 ∙ by Emily Alsentzer, et al. ∙ 20 ∙ share

read it
Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images

The rapidly emerging field of computational pathology has the potential ...
04/20/2020 ∙ by Ming Y. Lu, et al. ∙ 19 ∙ share

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...
05/05/2020 ∙ by Dongnan Liu, et al. ∙ 19 ∙ share

read it
Learning to Complement Humans

A rising vision for AI in the open world centers on the development of s...
05/01/2020 ∙ by Bryan Wilder, et al. ∙ 19 ∙ share

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...
12/18/2019 ∙ by Richard J. Chen, et al. ∙ 18 ∙ share

read it
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation

Fully convolutional neural networks (FCNs), and in particular U-Nets, ha...
11/29/2019 ∙ by Alireza Mehrtash, et al. ∙ 17 ∙ share

read it
Neuroscience-inspired online unsupervised learning algorithms

Although the currently popular deep learning networks achieve unpreceden...
08/05/2019 ∙ by Cengiz Pehlevan, et al. ∙ 16 ∙ share

read it
Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks

Solutions to differential equations are of significant scientific and en...
07/21/2020 ∙ by Dylan Randle, et al. ∙ 16 ∙ share

read it
A Topological Nomenclature for 3D Shape Analysis in Connectomics

An essential task in nano-scale connectomics is the morphology analysis ...
09/27/2019 ∙ by Abhimanyu Talwar, et al. ∙ 15 ∙ share

read it
Emergent Properties of Foveated Perceptual Systems

We introduce foveated perceptual systems, inspired by human biological s...
06/14/2020 ∙ by Arturo Deza, et al. ∙ 15 ∙ share

read it
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images

Supervised deep learning algorithms have enabled significant performance...
12/19/2018 ∙ by Bruno Lecouat, et al. ∙ 14 ∙ share

read it
Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging

Fetal magnetic resonance imaging (MRI) is challenged by uncontrollable, ...
09/25/2019 ∙ by Ayush Singh, et al. ∙ 13 ∙ share

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...
12/04/2019 ∙ by Preetum Nakkiran, et al. ∙ 13 ∙ share

read it
Learning to Prune: Speeding up Repeated Computations

It is common to encounter situations where one must solve a sequence of ...
04/26/2019 ∙ by Daniel Alabi, et al. ∙ 12 ∙ share

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 ...
04/27/2020 ∙ by Haoran Dou, et al. ∙ 12 ∙ share

read it
Too many cooks: Coordinating multi-agent collaboration through inverse planning

Collaboration requires agents to coordinate their behavior on the fly, s...
03/26/2020 ∙ by Rose E. Wang, et al. ∙ 11 ∙ share

read it
Collapsing Bandits and Their Application to Public Health Interventions

We propose and study Collpasing Bandits, a new restless multi-armed band...
07/05/2020 ∙ by Aditya Mate, et al. ∙ 11 ∙ share

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...
10/05/2018 ∙ by Dufan Wu, et al. ∙ 10 ∙ share

read it
Thwarting Adversarial Examples: An L_0-RobustSparse Fourier Transform

We give a new algorithm for approximating the Discrete Fourier transform...
12/12/2018 ∙ by Mitali Bafna, et al. ∙ 10 ∙ share

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...
06/19/2020 ∙ by Davood Karimi, et al. ∙ 10 ∙ share

read it
Fast, Structured Clinical Documentation via Contextual Autocomplete

We present a system that uses a learned autocompletion mechanism to faci...
07/29/2020 ∙ by Divya Gopinath, et al. ∙ 9 ∙ share

read it
Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?

Commercial iterative reconstruction techniques on modern CT scanners tar...
11/08/2018 ∙ by Hongming Shan, et al. ∙ 8 ∙ share

read it
Seeing in the dark with recurrent convolutional neural networks

Classical convolutional neural networks (cCNNs) are very good at categor...
11/21/2018 ∙ by Till S. Hartmann, et al. ∙ 8 ∙ share

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...
04/01/2019 ∙ by Ramy Baly, et al. ∙ 8 ∙ share

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...
10/05/2019 ∙ by Vivek Sharma, et al. ∙ 8 ∙ share

read it
A Learning Strategy for Contrast-agnostic MRI Segmentation

We present a deep learning strategy that enables, for the first time, co...
03/04/2020 ∙ by Benjamin Billot, et al. ∙ 8 ∙ share

read it
Online Residential Demand Response via Contextual Multi-Armed Bandits

Residential load demands have huge potential to be exploited to enhance ...
03/07/2020 ∙ by Xin Chen, et al. ∙ 8 ∙ share

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...
06/11/2020 ∙ by Mo Tiwari, et al. ∙ 8 ∙ share

read it
Smarter Parking: Using AI to Identify Parking Inefficiencies in Vancouver

On-street parking is convenient, but has many disadvantages: on-street s...
03/21/2020 ∙ by Devon Graham, et al. ∙ 7 ∙ share

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 ...
05/29/2020 ∙ by Nishanth Thumbavanam Arun, et al. ∙ 7 ∙ share

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...
05/30/2020 ∙ by Jianqiang Wan, et al. ∙ 7 ∙ share

read it
Self-Organization and Artificial Life

Self-organization can be broadly defined as the ability of a system to d...
03/14/2019 ∙ by Carlos Gershenson, et al. ∙ 6 ∙ share

read it
Generative-based Airway and Vessel Morphology Quantification on Chest CT Images

Accurately and precisely characterizing the morphology of small pulmonar...
02/13/2020 ∙ by Pietro Nardelli, et al. ∙ 6 ∙ share

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...
04/08/2020 ∙ by Dianbo Liu, et al. ∙ 6 ∙ share

read it
A Large Dataset of Historical Japanese Documents with Complex Layouts

Deep learning-based approaches for automatic document layout analysis an...
04/18/2020 ∙ by Zejiang Shen, et al. ∙ 6 ∙ share

read it
CheckNet: Secure Inference on Untrusted Devices

We introduce CheckNet, a method for secure inference with deep neural ne...
06/17/2019 ∙ by Marcus Comiter, et al. ∙ 5 ∙ share

read it
Generalized Principal Component Analysis

Generalized principal component analysis (GLM-PCA) facilitates dimension...
07/03/2019 ∙ by F. William Townes, et al. ∙ 5 ∙ share

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...
08/02/2019 ∙ by Aman Rana, et al. ∙ 5 ∙ share

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 ...
07/31/2019 ∙ by Fan-Yun Sun, et al. ∙ 5 ∙ share

read it
Exploiting Parallelism Opportunities with Deep Learning Frameworks

State-of-the-art machine learning frameworks support a wide variety of d...
08/13/2019 ∙ by Yu Emma Wang, et al. ∙ 5 ∙ share

read it
Regional Tree Regularization for Interpretability in Black Box Models

The lack of interpretability remains a barrier to the adoption of deep n...
08/13/2019 ∙ by Mike Wu, et al. ∙ 5 ∙ share

read it
Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures

Generative models have achieved impressive results in many domains inclu...
09/03/2019 ∙ by Jordan Hoffmann, et al. ∙ 5 ∙ share

read it