Johns Hopkins University

research

∙ 08/31/2021

When are Deep Networks really better than Random Forests at small sample sizes?

Random forests (RF) and deep networks (DN) are two of the most popular m...

Haoyin Xu, et al. ∙

research

∙ 09/29/2021

Towards a theory of out-of-distribution learning

What is learning? 20^st century formalizations of learning theory – whic...

Ali Geisa, et al. ∙

research

∙ 12/20/2019

C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation

3D convolution neural networks (CNN) have been proved very successful in...

Qihang Yu, et al. ∙

research

∙ 04/27/2020

A general approach to progressive intelligence

In biological learning, data is used to improve performance on the task ...

Joshua T. Vogelstein, et al. ∙

research

∙ 02/09/2022

A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems

Constructing surrogate models for uncertainty quantification (UQ) on com...

Katiana Kontolati, et al. ∙

research

∙ 12/27/2019

The Chi-Square Test of Distance Correlation

Distance correlation has gained much recent attention in the statistics ...

Cencheng Shen, et al. ∙

research

∙ 02/03/2022

Mapping DNN Embedding Manifolds for Network Generalization Prediction

Understanding Deep Neural Network (DNN) performance in changing conditio...

Molly O'Brien, et al. ∙

research

∙ 05/14/2021

Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction

When language models process syntactically complex sentences, do they us...

Shauli Ravfogel, et al. ∙

research

∙ 03/20/2019

OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations

We present a novel model called OCGAN for the classical problem of one-c...

Pramuditha Perera, et al. ∙

research

∙ 04/24/2019

Deep Sparse Representation-based Classification

We present a transductive deep learning-based formulation for the sparse...

Mahdi Abavisani, et al. ∙

research

∙ 09/23/2019

Pelvis Surface Estimation From Partial CT for Computer-Aided Pelvic Osteotomies

Computer-aided surgical systems commonly use preoperative CT scans when ...

Robert Grupp, et al. ∙

research

∙ 12/02/2019

Pyramid Convolutional RNN for MRI Reconstruction

Fast and accurate MRI image reconstruction from undersampled data is cri...

Puyang Wang, et al. ∙

research

∙ 11/09/2021

Graph Matching via Optimal Transport

The graph matching problem seeks to find an alignment between the nodes ...

Ali Saad-Eldin, et al. ∙

research

∙ 12/17/2019

Learning from Synthetic Animals

Despite great success in human parsing, progress for parsing other defor...

Jiteng Mu, et al. ∙

research

∙ 03/07/2019

Deep CNN-based Multi-task Learning for Open-Set Recognition

We propose a novel deep convolutional neural network (CNN) based multi-t...

Poojan Oza, et al. ∙

research

∙ 07/15/2021

Only Train Once: A One-Shot Neural Network Training And Pruning Framework

Structured pruning is a commonly used technique in deploying deep neural...

Tianyi Chen, et al. ∙

research

∙ 10/13/2021

Fast Posterior Estimation of Cardiac Electrophysiological Model Parameters via Bayesian Active Learning

Probabilistic estimation of cardiac electrophysiological model parameter...

Md Shakil Zaman, et al. ∙

research

∙ 03/09/2022

On the influence of over-parameterization in manifold based surrogates and deep neural operators

Constructing accurate and generalizable approximators for complex physic...

Katiana Kontolati, et al. ∙

research

∙ 02/11/2020

Incremental Learning for Metric-Based Meta-Learners

Majority of the modern meta-learning methods for few-shot classification...

Qing Liu, et al. ∙

research

∙ 10/25/2021

Pediatric Otoscopy Video Screening with Shift Contrastive Anomaly Detection

Ear related concerns and symptoms represents the leading indication for ...

Weiyao Wang, et al. ∙

research

∙ 12/20/2019

AtomNAS: Fine-Grained End-to-End Neural Architecture Search

Designing of search space is a critical problem for neural architecture ...

Jieru Mei, et al. ∙

research

∙ 08/28/2019

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting

Crowd counting presents enormous challenges in the form of large variati...

Vishwanath A. Sindagi, et al. ∙

research

∙ 12/18/2019

Learning to Segment Brain Anatomy from 2D Ultrasound with Less Data

Automatic segmentation of anatomical landmarks from ultrasound (US) play...

Jeya Maria Jose V., et al. ∙

research

∙ 11/30/2020

Automating Artifact Detection in Video Games

In spite of advances in gaming hardware and software, gameplay is often ...

Parmida Davarmanesh, et al. ∙

research

∙ 08/04/2021

The Impact of Machine Learning on 2D/3D Registration for Image-guided Interventions: A Systematic Review and Perspective

Image-based navigation is widely considered the next frontier of minimal...

Mathias Unberath, et al. ∙

research

∙ 09/22/2021

Label Cleaning Multiple Instance Learning: Refining Coarse Annotations on Single Whole-Slide Images

Annotating cancerous regions in whole-slide images (WSIs) of pathology s...

Zhenzhen Wang, et al. ∙

research

∙ 07/26/2021

Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP

We introduce a method that allows to automatically segment images into s...

Daniil Pakhomov, et al. ∙

research

∙ 06/12/2022

A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games

Algorithms designed for single-agent reinforcement learning (RL) general...

Samuel Sokota, et al. ∙

research

∙ 09/09/2019

TDAPNet: Prototype Network with Recurrent Top-Down Attention for Robust Object Classification under Partial Occlusion

Despite deep convolutional neural networks' great success in object clas...

Mingqing Xiao, et al. ∙

research

∙ 11/28/2018

Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints from Limited Training Data

Detecting semantic parts of an object is a challenging task in computer ...

Yutong Bai, et al. ∙

research

∙ 01/03/2019

CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions

Referring object detection and referring image segmentation are importan...

Runtao Liu, et al. ∙

research

∙ 04/02/2019

C2AE: Class Conditioned Auto-Encoder for Open-set Recognition

Models trained for classification often assume that all testing classes ...

Poojan Oza, et al. ∙

research

∙ 12/20/2019

Dependable Neural Networks for Safety Critical Tasks

Neural Networks are being integrated into safety critical systems, e.g.,...

Molly O'Brien, et al. ∙

research

∙ 12/05/2020

Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks

We propose the Poisson neural networks (PNNs) to learn Poisson systems a...

Pengzhan Jin, et al. ∙

research

∙ 01/20/2022

Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models

The advent of transformer-based models such as BERT has led to the rise ...

Suraj Nair, et al. ∙

research

∙ 11/29/2019

Prior-based Domain Adaptive Object Detection for Adverse Weather Conditions

Adverse weather conditions such as rain and haze corrupt the quality of ...

Vishwanath A. Sindagi, et al. ∙

research

∙ 04/05/2022

SwapMix: Diagnosing and Regularizing the Over-Reliance on Visual Context in Visual Question Answering

While Visual Question Answering (VQA) has progressed rapidly, previous w...

Vipul Gupta, et al. ∙

research

∙ 08/22/2018

Rethinking Monocular Depth Estimation with Adversarial Training

Monocular depth estimation is an extensively studied computer vision pro...

Richard Chen, et al. ∙

research

∙ 03/12/2019

Communication-efficient distributed SGD with Sketching

Large-scale distributed training of neural networks is often limited by ...

Nikita Ivkin, et al. ∙

research

∙ 04/02/2019

MVX-Net: Multimodal VoxelNet for 3D Object Detection

Many recent works on 3D object detection have focused on designing neura...

Vishwanath A. Sindagi, et al. ∙

research

∙ 04/30/2019

Structured Prediction using cGANs with Fusion Discriminator

We propose the fusion discriminator, a single unified framework for inco...

Faisal, et al. ∙

research

∙ 07/03/2020

A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces

The problem of linking functional connectomics to behavior is extremely ...

Niharika Shimona D'Souza, et al. ∙

research

∙ 12/12/2020

Mapping the Timescale Organization of Neural Language Models

In the human brain, sequences of language input are processed within a d...

Hsiang-Yun Sherry Chien, et al. ∙

research

∙ 02/04/2021

An efficient optimization based microstructure reconstruction approach with multiple loss functions

Stochastic microstructure reconstruction involves digital generation of ...

Anindya Bhaduri, et al. ∙

research

∙ 10/16/2021

Streaming Decision Trees and Forests

Machine learning has successfully leveraged modern data and provided com...

Haoyin Xu, et al. ∙

research

∙ 03/04/2020

Spatiotemporal-Aware Augmented Reality: Redefining HCI in Image-Guided Therapy

Suboptimal interaction with patient data and challenges in mastering 3D ...

Javad Fotouhi, et al. ∙

research

∙ 06/11/2020

Understanding Human Hands in Contact at Internet Scale

Hands are the central means by which humans manipulate their world and b...

Dandan Shan, et al. ∙

research

∙ 07/02/2020

Multi-resolution Super Learner for Voxel-wise Classification of Prostate Cancer Using Multi-parametric MRI

While current research has shown the importance of Multi-parametric MRI ...

Jin Jin, et al. ∙

research

∙ 08/09/2021

PASS: Protected Attribute Suppression System for Mitigating Bias in Face Recognition

Face recognition networks encode information about sensitive attributes ...

Prithviraj Dhar, et al. ∙

research

∙ 11/30/2021

SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches

Sketch-based image manipulation is an interactive image editing task to ...

Yu Zeng, et al. ∙

Johns Hopkins University

Featured Researchers