
Efficient Object Detection in Large Images using Deep Reinforcement Learning
Traditionally, an object detector is applied to every part of the scene ...
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Stable Prediction with Model Misspecification and Agnostic Distribution Shift
For many machine learning algorithms, two main assumptions are required ...
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PyTorch: An Imperative Style, HighPerformance Deep Learning Library
Deep learning frameworks have often focused on either usability or speed...
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Regression Planning Networks
Recent learningtoplan methods have shown promising results on planning...
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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...
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DermGAN: Synthetic Generation of Clinical Skin Images with Pathology
Despite the recent success in applying supervised deep learning to medic...
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Evaluating the Disentanglement of Deep Generative Models through Manifold Topology
Learning disentangled representations is regarded as a fundamental task ...
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Computational model discovery with reinforcement learning
The motivation of this study is to leverage recent breakthroughs in arti...
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Deep Bayesian Active Learning for Multiple Correct Outputs
Typical active learning strategies are designed for tasks, such as class...
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Local Linear Forests
Random forests are a powerful method for nonparametric regression, but ...
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4D SpatioTemporal ConvNets: Minkowski Convolutional Neural Networks
In many robotics and VR/AR applications, 3Dvideos are readilyavailable...
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Learning by Abstraction: The Neural State Machine
We introduce the Neural State Machine, seeking to bridge the gap between...
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Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences
Reward functions are a common way to specify the objective of a robot. A...
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TransGaGa: GeometryAware Unsupervised ImagetoImage Translation
Unsupervised imagetoimage translation aims at learning a mapping betwe...
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cFineGAN: Unsupervised multiconditional finegrained image generation
We propose an unsupervised multiconditional image generation pipeline: ...
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Adversarial Representation Active Learning
Active learning aims to develop labelefficient algorithms by querying t...
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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...
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A Meanfield Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth
Training deep neural networks with stochastic gradient descent (SGD) can...
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MetaReinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling
Reinforcement learning algorithms can acquire policies for complex tasks...
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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...
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ImagineNet: Restyling Apps Using Neural Style Transfer
This paper presents ImagineNet, a tool that uses a novel neural style tr...
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Hierarchical Reinforcement Learning with AdvantageBased Auxiliary Rewards
Hierarchical Reinforcement Learning (HRL) is a promising approach to sol...
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Action Genome: Actions as Composition of Spatiotemporal Scene Graphs
Action recognition has typically treated actions and activities as monol...
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Neural Network Generalization: The impact of camera parameters
We quantify the generalization of a convolutional neural network (CNN) t...
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Roundtrip: A Deep Generative Neural Density Estimator
Density estimation is a fundamental problem in both statistics and machi...
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Visual Relationships as Functions: Enabling FewShot Scene Graph Prediction
Scene graph prediction  classifying the set of objects and predicates...
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Compositional Explanations of Neurons
We describe a procedure for explaining neurons in deep representations b...
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Generative 3D Part Assembly via Dynamic Graph Learning
Autonomous part assembly is a challenging yet crucial task in 3D compute...
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Convex Hierarchical Clustering for GraphStructured Data
Convex clustering is a recent stable alternative to hierarchical cluster...
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Automatically Neutralizing Subjective Bias in Text
Texts like news, encyclopedias, and some social media strive for objecti...
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Separating the Effects of Batch Normalization on CNN Training Speed and Stability Using Classical Adaptive Filter Theory
Batch Normalization (BatchNorm) is commonly used in Convolutional Neural...
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Sufficient Representations for Categorical Variables
Many learning algorithms require categorical data to be transformed into...
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Asking Easy Questions: A UserFriendly Approach to Active Reward Learning
Robots can learn the right reward function by querying a human expert. E...
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Question Type Classification Methods Comparison
The paper presents a comparative study of stateoftheart approaches fo...
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Design Space for Graph Neural Networks
The rapid evolution of Graph Neural Networks (GNNs) has led to a growing...
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Pretraining Graph Neural Networks
Many applications of machine learning in science and medicine, including...
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Online Model Distillation for Efficient Video Inference
Highquality computer vision models typically address the problem of und...
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MultiAgent Deep Reinforcement Learning for Largescale Traffic Signal Control
Reinforcement learning (RL) is a promising datadriven approach for adap...
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AirSim Drone Racing Lab
Autonomous drone racing is a challenging research problem at the interse...
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Imitation Learning for Human Pose Prediction
Modeling and prediction of human motion dynamics has long been a challen...
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Datadependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation
Existing Rademacher complexity bounds for neural networks rely only on n...
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Accelerating cardiac cine MRI beyond compressed sensing using DLESPIRiT
A novel neural network architecture, known as DLESPIRiT, is proposed to...
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MetaLearning without Memorization
The ability to learn new concepts with small amounts of data is a critic...
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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...
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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...
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SelfSupervised Learning of State Estimation for Manipulating Deformable Linear Objects
We demonstrate modelbased, visual robot manipulation of linear deformab...
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Predicting the Physical Dynamics of Unseen 3D Objects
Machines that can predict the effect of physical interactions on the dyn...
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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...
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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...
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Dynamic MultiRobot Task Allocation under Uncertainty and Temporal Constraints
We consider the problem of dynamically allocating tasks to multiple agen...
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