University of Michigan

research

∙ 09/04/2019

Towards Automatic Detection of Misinformation in Online Medical Videos

Recent years have witnessed a significant increase in the online sharing...

Rui Hou, et al. ∙

research

∙ 06/16/2022

OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology

Accurate intraoperative diagnosis is essential for providing safe and ef...

Cheng Jiang, et al. ∙

research

∙ 10/02/2019

Attacking Vision-based Perception in End-to-End Autonomous Driving Models

Recent advances in machine learning, especially techniques such as deep ...

Adith Boloor, et al. ∙

research

∙ 05/08/2019

Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances

Emotion is intrinsic to humans and consequently emotion understanding is...

Soujanya Poria, et al. ∙

research

∙ 05/28/2020

Deep Learning for Automatic Pneumonia Detection

Pneumonia is the leading cause of death among young children and one of ...

Tatiana Gabruseva, et al. ∙

research

∙ 01/17/2019

AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving

Decision making in automated driving is highly specific to the environme...

Sumanth Chennupati, et al. ∙

research

∙ 07/26/2020

OASIS: A Large-Scale Dataset for Single Image 3D in the Wild

Single-view 3D is the task of recovering 3D properties such as depth and...

Weifeng Chen, et al. ∙

research

∙ 12/11/2019

What Can Learned Intrinsic Rewards Capture?

Reinforcement learning agents can include different components, such as ...

Zeyu Zheng, et al. ∙

research

∙ 03/21/2020

Monocular Depth Prediction Through Continuous 3D Loss

This paper reports a new continuous 3D loss function for learning depth ...

Minghan Zhu, et al. ∙

research

∙ 09/23/2019

Shadow Transfer: Single Image Relighting For Urban Road Scenes

Illumination effects in images, specifically cast shadows and shading, h...

Alexandra Carlson, et al. ∙

research

∙ 09/06/2021

Detecting Inspiring Content on Social Media

Inspiration moves a person to see new possibilities and transforms the w...

Oana Ignat, et al. ∙

research

∙ 11/17/2021

Learning to Compose Visual Relations

The visual world around us can be described as a structured set of objec...

Nan Liu, et al. ∙

research

∙ 02/20/2021

On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning

Model-agnostic meta-learning (MAML) has emerged as one of the most succe...

Ren Wang, et al. ∙

research

∙ 09/24/2019

Unified Vision-Language Pre-Training for Image Captioning and VQA

This paper presents a unified Vision-Language Pre-training (VLP) model. ...

Luowei Zhou, et al. ∙

research

∙ 12/11/2019

Near-optimal Oracle-efficient Algorithms for Stationary and Non-Stationary Stochastic Linear Bandits

We investigate the design of two algorithms that enjoy not only computat...

Baekjin Kim, et al. ∙

research

∙ 12/15/2019

How Should an Agent Practice?

We present a method for learning intrinsic reward functions to drive the...

Janarthanan Rajendran, et al. ∙

research

∙ 05/08/2020

Project and Forget: Solving Large-Scale Metric Constrained Problems

Given a set of dissimilarity measurements amongst data points, determini...

Rishi Sonthalia, et al. ∙

research

∙ 11/19/2019

Eliminating artefacts in Polarimetric Images using Deep Learning

Polarization measurements done using Imaging Polarimeters such as the Ro...

Dhruv Paranjpye, et al. ∙

research

∙ 05/18/2020

Scaling-up Distributed Processing of Data Streams for Machine Learning

Emerging applications of machine learning in numerous areas involve cont...

Matthew Nokleby, et al. ∙

research

∙ 06/11/2020

VirTex: Learning Visual Representations from Textual Annotations

The de-facto approach to many vision tasks is to start from pretrained v...

Karan Desai, et al. ∙

research

∙ 06/26/2021

Inverting and Understanding Object Detectors

As a core problem in computer vision, the performance of object detectio...

Ang Cao, et al. ∙

research

∙ 12/08/2021

Merging Subject Matter Expertise and Deep Convolutional Neural Network for State-Based Online Machine-Part Interaction Classification

Machine-part interaction classification is a key capability required by ...

Hao Wang, 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

∙ 09/10/2021

Beyond the Tip of the Iceberg: Assessing Coherence of Text Classifiers

As large-scale, pre-trained language models achieve human-level and supe...

Shane Storks, et al. ∙

research

∙ 03/12/2019

Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models

Recent advances in machine learning, especially techniques such as deep ...

Adith Boloor, et al. ∙

research

∙ 12/17/2019

HCNAF: Hyper-Conditioned Neural Autoregressive Flow and its Application for Probabilistic Occupancy Map Forecasting

We introduce Hyper-Conditioned Neural Autoregressive Flow (HCNAF); a pow...

Jean-Sebastien Valois, et al. ∙

research

∙ 03/23/2020

What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization

Knowledge graphs (KGs) store highly heterogeneous information about the ...

Caleb Belth, et al. ∙

research

∙ 07/30/2020

G-CREWE: Graph CompREssion With Embedding for Network Alignment

Network alignment is useful for multiple applications that require incre...

Kyle K. Qin, et al. ∙

research

∙ 09/18/2021

PCNN: A physics-constrained neural network for multiphase flows

The present study develops a physics-constrained neural network (PCNN) t...

Haoyang Zheng, et al. ∙

research

∙ 12/27/2019

Efficient Adversarial Training with Transferable Adversarial Examples

Adversarial training is an effective defense method to protect classific...

Haizhong Zheng, et al. ∙

research

∙ 02/25/2020

Sparsity-promoting algorithms for the discovery of informative Koopman invariant subspaces

Koopman decomposition is a non-linear generalization of eigen decomposit...

Shaowu Pan, et al. ∙

research

∙ 05/15/2020

On Learnability under General Stochastic Processes

Statistical learning theory under independent and identically distribute...

A. Philip Dawid, et al. ∙

research

∙ 08/06/2021

Dynamic Semantic Occupancy Mapping using 3D Scene Flow and Closed-Form Bayesian Inference

This paper reports on a dynamic semantic mapping framework that incorpor...

Aishwarya Unnikrishnan, et al. ∙

research

∙ 09/06/2021

STaCK: Sentence Ordering with Temporal Commonsense Knowledge

Sentence order prediction is the task of finding the correct order of se...

Deepanway Ghosal, et al. ∙

research

∙ 01/05/2022

Fusing Convolutional Neural Network and Geometric Constraint for Image-based Indoor Localization

This paper proposes a new image-based localization framework that explic...

Jingwei Song, et al. ∙

research

∙ 04/15/2022

CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection

Single-particle cryo-electron microscopy (cryo-EM) has become one of the...

Quanfu Fan, et al. ∙

research

∙ 07/16/2019

Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving

In Autonomous Vehicles (AVs), one fundamental pillar is perception, whic...

Yulong Cao, et al. ∙

research

∙ 02/08/2020

BRPO: Batch Residual Policy Optimization

In batch reinforcement learning (RL), one often constrains a learned pol...

Sungryull Sohn, et al. ∙

research

∙ 06/05/2020

Novel Object Viewpoint Estimation through Reconstruction Alignment

The goal of this paper is to estimate the viewpoint for a novel object. ...

Mohamed El Banani, et al. ∙

research

∙ 08/08/2021

Contrastive Representation Learning for Rapid Intraoperative Diagnosis of Skull Base Tumors Imaged Using Stimulated Raman Histology

Background: Accurate diagnosis of skull base tumors is essential for pro...

Cheng Jiang, et al. ∙

research

∙ 09/14/2021

Non-linear Independent Dual System (NIDS) for Discretization-independent Surrogate Modeling over Complex Geometries

Numerical solutions of partial differential equations (PDEs) require exp...

James Duvall, et al. ∙

research

∙ 09/15/2021

Disentangling Generative Factors of Physical Fields Using Variational Autoencoders

The ability to extract generative parameters from high-dimensional field...

Christian Jacobsen, et al. ∙

research

∙ 09/24/2021

An animated picture says at least a thousand words: Selecting Gif-based Replies in Multimodal Dialog

Online conversations include more than just text. Increasingly, image-ba...

Xingyao Wang, et al. ∙

research

∙ 12/15/2021

Feature-Attending Recurrent Modules for Generalization in Reinforcement Learning

Deep reinforcement learning (Deep RL) has recently seen significant prog...

Wilka Carvalho, et al. ∙

research

∙ 04/29/2022

A suite of diagnostic metrics for characterizing selection schemes

Evolutionary algorithms are effective general-purpose techniques for sol...

Jose Guadalupe Hernandez, et al. ∙

research

∙ 08/07/2018

Rethinking Numerical Representations for Deep Neural Networks

With ever-increasing computational demand for deep learning, it is criti...

Parker Hill, et al. ∙

research

∙ 12/19/2018

D3D: Distilled 3D Networks for Video Action Recognition

State-of-the-art methods for video action recognition commonly use an en...

Jonathan C. Stroud, et al. ∙

research

∙ 09/03/2019

Face-to-Parameter Translation for Game Character Auto-Creation

Character customization system is an important component in Role-Playing...

Tianyang Shi, et al. ∙

research

∙ 05/08/2020

Tree! I am no Tree! I am a Low Dimensional Hyperbolic Embedding

Given data, finding a faithful low-dimensional hyperbolic embedding of t...

Rishi Sonthalia, et al. ∙

research

∙ 06/02/2020

On the Equivalence between Online and Private Learnability beyond Binary Classification

Alon et al. [2019] and Bun et al. [2020] recently showed that online lea...

Young Hun Jung, et al. ∙

University of Michigan

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