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
265 publications
Rui Wang
123 publications
Hao Wang
109 publications
Xiang Li
70 publications
Finale Doshi-Velez
56 publications
Fan Zhang
53 publications
José Miguel Hernández-Lobato
50 publications
Xin Chen
48 publications
Alexander M. Rush
46 publications
Ryan P. Adams
45 publications
James Zou
45 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. ∙ 33 ∙ share

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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. ∙ 11 ∙ share

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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Generalized Principal Component Analysis

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

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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

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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

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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

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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

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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

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Learning to Seek: Autonomous Source Seeking with Deep Reinforcement Learning Onboard a Nano Drone Microcontroller

Fully autonomous navigation using nano drones has numerous application i...
09/25/2019 ∙ by Bardienus P. Duisterhof, et al. ∙ 5 ∙ share

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Predicting Electron-Ionization Mass Spectrometry using Neural Networks

When confronted with a substance of unknown identity, researchers often ...
11/21/2018 ∙ by Jennifer N. Wei, et al. ∙ 4 ∙ share

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Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions

When the average performance of a prediction model varies significantly ...
01/29/2019 ∙ by Hao Wang, et al. ∙ 4 ∙ share

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Knowledge-based Analysis for Mortality Prediction from CT Images

Recent studies have highlighted the high correlation between cardiovascu...
02/20/2019 ∙ by Hengtao Guo, et al. ∙ 4 ∙ share

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Beyond Imitation: Generative and Variational Choreography via Machine Learning

Our team of dance artists, physicists, and machine learning researchers ...
07/11/2019 ∙ by Mariel Pettee, et al. ∙ 4 ∙ share

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Automatic Registration between Cone-Beam CT and Scanned Surface via Deep-Pose Regression Neural Networks and Clustered Similarities

Computerized registration between maxillofacial cone-beam computed tomog...
07/29/2019 ∙ by Minyoung Chung, et al. ∙ 4 ∙ share

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Finding Friend and Foe in Multi-Agent Games

Recent breakthroughs in AI for multi-agent games like Go, Poker, and Dot...
06/05/2019 ∙ by Jack Serrino, et al. ∙ 3 ∙ share

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Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes

In this paper, we theoretically prove that gradient descent can find a g...
08/05/2019 ∙ by Kenji Kawaguchi, et al. ∙ 3 ∙ share

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Defining AI in Policy versus Practice

Recent concern about harms of information technologies motivate consider...
12/23/2019 ∙ by P. M. Krafft, et al. ∙ 3 ∙ share

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DeepSPINE: Automated Lumbar Vertebral Segmentation, Disc-level Designation, and Spinal Stenosis Grading Using Deep Learning

The high prevalence of spinal stenosis results in a large volume of MRI ...
07/26/2018 ∙ by Jen-Tang Lu, et al. ∙ 2 ∙ share

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Synthetically Trained Icon Proposals for Parsing and Summarizing Infographics

Widely used in news, business, and educational media, infographics are h...
07/27/2018 ∙ by Spandan Madan, et al. ∙ 2 ∙ share

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