Stanford University

∙ Stanford , United States ∙ 0 followers

Stanford University, one of the world's leading teaching and research universities, is dedicated to finding solutions to big challenges and to preparing students for leadership in a complex world.

Featured Researchers

Sergey Levine
178 publications
Hao Wang
98 publications
Li Fei-Fei
96 publications
Rui Wang
93 publications
Jian Zhang
83 publications
Stefano Ermon
80 publications
Silvio Savarese
79 publications
Percy Liang
78 publications
Jure Leskovec
71 publications
Li Zhang
68 publications
Michael W. Mahoney
68 publications

Efficient Object Detection in Large Images using Deep Reinforcement Learning

Traditionally, an object detector is applied to every part of the scene ...
12/09/2019 ∙ by Burak Uzkent, et al. ∙ 98 ∙ share

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Stable Prediction with Model Misspecification and Agnostic Distribution Shift

For many machine learning algorithms, two main assumptions are required ...
01/31/2020 ∙ by Kun Kuang, et al. ∙ 95 ∙ share

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PyTorch: An Imperative Style, High-Performance Deep Learning Library

Deep learning frameworks have often focused on either usability or speed...
12/03/2019 ∙ by Adam Paszke, et al. ∙ 90 ∙ share

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Regression Planning Networks

Recent learning-to-plan methods have shown promising results on planning...
09/28/2019 ∙ by Danfei Xu, et al. ∙ 87 ∙ share

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An Application of Generative Adversarial Networks for Super Resolution Medical Imaging

Acquiring High Resolution (HR) Magnetic Resonance (MR) images requires t...
12/19/2019 ∙ by Rewa Sood, et al. ∙ 68 ∙ share

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DermGAN: Synthetic Generation of Clinical Skin Images with Pathology

Despite the recent success in applying supervised deep learning to medic...
11/20/2019 ∙ by Amirata Ghorbani, et al. ∙ 66 ∙ share

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Computational model discovery with reinforcement learning

The motivation of this study is to leverage recent breakthroughs in arti...
12/29/2019 ∙ by Maxime Bassenne, et al. ∙ 58 ∙ share

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Deep Bayesian Active Learning for Multiple Correct Outputs

Typical active learning strategies are designed for tasks, such as class...
12/02/2019 ∙ by Khaled Jedoui, et al. ∙ 53 ∙ share

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Local Linear Forests

Random forests are a powerful method for non-parametric regression, but ...
07/30/2018 ∙ by Rina Friedberg, et al. ∙ 52 ∙ share

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4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks

In many robotics and VR/AR applications, 3D-videos are readily-available...
04/18/2019 ∙ by Christopher Choy, et al. ∙ 50 ∙ share

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Learning by Abstraction: The Neural State Machine

We introduce the Neural State Machine, seeking to bridge the gap between...
07/09/2019 ∙ by Drew A. Hudson, et al. ∙ 49 ∙ share

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TransGaGa: Geometry-Aware Unsupervised Image-to-Image Translation

Unsupervised image-to-image translation aims at learning a mapping betwe...
04/21/2019 ∙ by Wayne Wu, et al. ∙ 48 ∙ share

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cFineGAN: Unsupervised multi-conditional fine-grained image generation

We propose an unsupervised multi-conditional image generation pipeline: ...
12/06/2019 ∙ by Gunjan Aggarwal, et al. ∙ 48 ∙ share

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Adversarial Representation Active Learning

Active learning aims to develop label-efficient algorithms by querying t...
12/20/2019 ∙ by Ali Mottaghi, et al. ∙ 44 ∙ share

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Predicting Regression Probability Distributions with Imperfect Data Through Optimal Transformations

The goal of regression analysis is to predict the value of a numeric out...
01/27/2020 ∙ by Jerome H. Friedman, et al. ∙ 42 ∙ share

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Automating Interpretability: Discovering and Testing Visual Concepts Learned by Neural Networks

Interpretability has become an important topic of research as more machi...
02/07/2019 ∙ by Amirata Ghorbani, et al. ∙ 40 ∙ share

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ImagineNet: Restyling Apps Using Neural Style Transfer

This paper presents ImagineNet, a tool that uses a novel neural style tr...
01/14/2020 ∙ by Michael H. Fischer, et al. ∙ 38 ∙ share

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Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards

Hierarchical Reinforcement Learning (HRL) is a promising approach to sol...
10/10/2019 ∙ by Siyuan Li, et al. ∙ 37 ∙ share

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Action Genome: Actions as Composition of Spatio-temporal Scene Graphs

Action recognition has typically treated actions and activities as monol...
12/15/2019 ∙ by Jingwei Ji, et al. ∙ 35 ∙ share

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Neural Network Generalization: The impact of camera parameters

We quantify the generalization of a convolutional neural network (CNN) t...
12/08/2019 ∙ by Zhenyi Liu, et al. ∙ 33 ∙ share

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Visual Relationships as Functions: Enabling Few-Shot Scene Graph Prediction

Scene graph prediction --- classifying the set of objects and predicates...
06/12/2019 ∙ by Apoorva Dornadula, et al. ∙ 29 ∙ share

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Convex Hierarchical Clustering for Graph-Structured Data

Convex clustering is a recent stable alternative to hierarchical cluster...
11/08/2019 ∙ by Claire Donnat, et al. ∙ 26 ∙ share

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Automatically Neutralizing Subjective Bias in Text

Texts like news, encyclopedias, and some social media strive for objecti...
11/21/2019 ∙ by Reid Pryzant, et al. ∙ 26 ∙ share

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Sufficient Representations for Categorical Variables

Many learning algorithms require categorical data to be transformed into...
08/26/2019 ∙ by Jonathan Johannemann, et al. ∙ 25 ∙ share

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Question Type Classification Methods Comparison

The paper presents a comparative study of state-of-the-art approaches fo...
01/03/2020 ∙ by Tamirlan Seidakhmetov, et al. ∙ 24 ∙ share

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Asking Easy Questions: A User-Friendly Approach to Active Reward Learning

Robots can learn the right reward function by querying a human expert. E...
10/10/2019 ∙ by Erdem Bıyık, et al. ∙ 23 ∙ share

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Online Model Distillation for Efficient Video Inference

High-quality computer vision models typically address the problem of und...
12/06/2018 ∙ by Ravi Teja Mullapudi, et al. ∙ 22 ∙ share

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Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control

Reinforcement learning (RL) is a promising data-driven approach for adap...
03/11/2019 ∙ by Tianshu Chu, et al. ∙ 22 ∙ share

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Pre-training Graph Neural Networks

Many applications of machine learning in science and medicine, including...
05/29/2019 ∙ by Weihua Hu, et al. ∙ 22 ∙ share

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Imitation Learning for Human Pose Prediction

Modeling and prediction of human motion dynamics has long been a challen...
09/08/2019 ∙ by Borui Wang, et al. ∙ 21 ∙ share

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Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation

Existing Rademacher complexity bounds for neural networks rely only on n...
05/09/2019 ∙ by Colin Wei, et al. ∙ 20 ∙ share

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Accelerating cardiac cine MRI beyond compressed sensing using DL-ESPIRiT

A novel neural network architecture, known as DL-ESPIRiT, is proposed to...
11/13/2019 ∙ by Christopher M. Sandino, et al. ∙ 19 ∙ share

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Meta-Learning without Memorization

The ability to learn new concepts with small amounts of data is a critic...
12/09/2019 ∙ by Mingzhang Yin, et al. ∙ 19 ∙ share

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Deep Optics for Monocular Depth Estimation and 3D Object Detection

Depth estimation and 3D object detection are critical for scene understa...
04/18/2019 ∙ by Julie Chang, et al. ∙ 18 ∙ share

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Playing Go without Game Tree Search Using Convolutional Neural Networks

The game of Go has a long history in East Asian countries, but the field...
07/02/2019 ∙ by Jeffrey Barratt, et al. ∙ 18 ∙ share

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Self-Supervised Learning of State Estimation for Manipulating Deformable Linear Objects

We demonstrate model-based, visual robot manipulation of linear deformab...
11/14/2019 ∙ by Mengyuan Yan, et al. ∙ 18 ∙ share

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Predicting the Physical Dynamics of Unseen 3D Objects

Machines that can predict the effect of physical interactions on the dyn...
01/16/2020 ∙ by Davis Rempe, et al. ∙ 18 ∙ share

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A Delay Metric for Video Object Detection: What Average Precision Fails to Tell

Average precision (AP) is a widely used metric to evaluate detection acc...
08/18/2019 ∙ by Huizi Mao, et al. ∙ 17 ∙ share

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How Relevant is the Turing Test in the Age of Sophisbots?

Popular culture has contemplated societies of thinking machines for gene...
08/30/2019 ∙ by Dan Boneh, et al. ∙ 17 ∙ share

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Generative Modeling by Estimating Gradients of the Data Distribution

We introduce a new generative model where samples are produced via Lange...
07/12/2019 ∙ by Yang Song, et al. ∙ 16 ∙ share

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Airbnb Price Prediction Using Machine Learning and Sentiment Analysis

Pricing a rental property on Airbnb is a challenging task for the owner ...
07/29/2019 ∙ by Pouya Rezazadeh Kalehbasti, et al. ∙ 16 ∙ share

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Efficient Graph Generation with Graph Recurrent Attention Networks

We propose a new family of efficient and expressive deep generative mode...
10/02/2019 ∙ by Renjie Liao, et al. ∙ 16 ∙ share

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Learning Temporal Action Proposals With Fewer Labels

Temporal action proposals are a common module in action detection pipeli...
10/03/2019 ∙ by Jingwei Ji, et al. ∙ 16 ∙ share

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Continuous Meta-Learning without Tasks

Meta-learning is a promising strategy for learning to efficiently learn ...
12/18/2019 ∙ by James Harrison, et al. ∙ 15 ∙ share

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Stable Prediction across Unknown Environments

In many important machine learning applications, the training distributi...
06/16/2018 ∙ by Kun Kuang, et al. ∙ 14 ∙ share

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Continual Learning via Neural Pruning

We introduce Continual Learning via Neural Pruning (CLNP), a new method ...
03/11/2019 ∙ by Siavash Golkar, et al. ∙ 14 ∙ share

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Tracking and Improving Information in the Service of Fairness

As algorithmic prediction systems have become widespread, fears that the...
04/22/2019 ∙ by Sumegha Garg, et al. ∙ 14 ∙ share

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Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery

Millions of people worldwide are absent from their country's census. Acc...
05/04/2019 ∙ by Wenjie Hu, et al. ∙ 14 ∙ share

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A Surprising Density of Illusionable Natural Speech

Recent work on adversarial examples has demonstrated that most natural i...
06/03/2019 ∙ by Melody Y. Guan, et al. ∙ 14 ∙ share

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Self-Driving Car Steering Angle Prediction Based on Image Recognition

Self-driving vehicles have expanded dramatically over the last few years...
12/11/2019 ∙ by Shuyang Du, et al. ∙ 14 ∙ share

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