
Streamlining Tensor and Network Pruning in PyTorch
In order to contrast the explosion in size of stateoftheart machine l...
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DeepXDE: A deep learning library for solving differential equations
Deep learning has achieved remarkable success in diverse applications; h...
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Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness
The accuracy of deep learning, i.e., deep neural networks, can be charac...
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15 Keypoints Is All You Need
Pose tracking is an important problem that requires identifying unique h...
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Unsupervised Deep Metric Learning via Auxiliary Rotation Loss
Deep metric learning is an important area due to its applicability to ma...
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Theory of Minds: Understanding Behavior in Groups Through Inverse Planning
Human social behavior is structured by relationships. We form teams, gro...
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Successor Features Support Modelbased and Modelfree Reinforcement Learning
One key challenge in reinforcement learning is the ability to generalize...
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Individual predictions matter: Assessing the effect of data ordering in training finetuned CNNs for medical imaging
We reproduced the results of CheXNet with fixed hyperparameters and 50 d...
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Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks
We propose the Poisson neural networks (PNNs) to learn Poisson systems a...
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A Caputo fractional derivativebased algorithm for optimization
We propose a novel Caputo fractional derivativebased optimization algor...
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Teaching with IMPACT
Like many problems in AI in their general form, supervised learning is c...
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Solving Inverse Stochastic Problems from Discrete Particle Observations Using the FokkerPlanck Equation and Physicsinformed Neural Networks
The FokkerPlanck (FP) equation governing the evolution of the probabili...
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PPINN: Parareal PhysicsInformed Neural Network for timedependent PDEs
Physicsinformed neural networks (PINNs) encode physical conservation la...
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The Efficiency of Human Cognition Reflects Planned Information Processing
Planning is useful. It lets people take actions that have desirable long...
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Wasserstein Adversarial Autoencoders for Knowledge Graph Embedding based DrugDrug Interaction Prediction
Interaction between pharmacological agents can trigger unexpected advers...
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Robot Object Retrieval with Contextual Natural Language Queries
Natural language object retrieval is a highly useful yet challenging tas...
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Recurrent neural circuits for contour detection
We introduce a deep recurrent neural network architecture that approxima...
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Metalearning PINN loss functions
We propose a metalearning technique for offline discovery of physicsin...
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Learning in Modal Space: Solving TimeDependent Stochastic PDEs Using PhysicsInformed Neural Networks
One of the open problems in scientific computing is the longtime integr...
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Stackelberg Punishment and BullyProofing Autonomous Vehicles
Mutually beneficial behavior in repeated games can be enforced via the t...
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Tracking Without Rerecognition in Humans and Machines
Imagine trying to track one particular fruitfly in a swarm of hundreds. ...
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Interactive Learning of Environment Dynamics for Sequential Tasks
In order for robots and other artificial agents to efficiently learn to ...
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Bootstrapping Motor Skill Learning with Motion Planning
Learning a robot motor skill from scratch is impractically slow; so much...
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Finding Options that Minimize Planning Time
While adding temporally abstract actions, or options, to an agent's acti...
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Trainability and Datadependent Initialization of Overparameterized ReLU Neural Networks
A neural network is said to be overspecified if its representational po...
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Potential Flow Generator with L_2 Optimal Transport Regularity for Generative Models
We propose a potential flow generator with L_2 optimal transport regular...
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RoomAcrossRoom: Multilingual VisionandLanguage Navigation with Dense Spatiotemporal Grounding
We introduce RoomAcrossRoom (RxR), a new VisionandLanguage Navigatio...
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A survey of statistical learning techniques as applied to inexpensive pediatric Obstructive Sleep Apnea data
Pediatric obstructive sleep apnea affects an estimated 15 elementarysc...
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Automatic Discovery and Optimization of Parts for Image Classification
Partbased representations have been shown to be very useful for image c...
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Joint and conditional estimation of tagging and parsing models
This paper compares two different ways of estimating statistical languag...
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Explaining away ambiguity: Learning verb selectional preference with Bayesian networks
This paper presents a Bayesian model for unsupervised learning of verb s...
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Learning Robust Dialog Policies in Noisy Environments
Modern virtual personal assistants provide a convenient interface for co...
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Implementing the Deep QNetwork
The Deep QNetwork proposed by Mnih et al. [2015] has become a benchmark...
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An Improved Training Procedure for Neural Autoregressive Data Completion
Neural autoregressive models are explicit density estimators that achiev...
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Deep Abstract QNetworks
We examine the problem of learning and planning on highdimensional doma...
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HardwareSoftware Codesign of Accurate, Multiplierfree Deep Neural Networks
While Deep Neural Networks (DNNs) push the stateoftheart in many mach...
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Summable Reparameterizations of Wasserstein Critics in the OneDimensional Setting
Generative adversarial networks (GANs) are an exciting alternative to al...
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Active Exploration for Learning Symbolic Representations
We introduce an online active exploration algorithm for dataefficiently...
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Mean Actor Critic
We propose a new algorithm, Mean ActorCritic (MAC), for discreteaction...
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Understanding the Impact of Precision Quantization on the Accuracy and Energy of Neural Networks
Deep neural networks are gaining in popularity as they are used to gener...
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Learning to Infer Graphics Programs from HandDrawn Images
We introduce a model that learns to convert simple hand drawings into gr...
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Runtime Configurable Deep Neural Networks for EnergyAccuracy Tradeoff
We present a novel dynamic configuration technique for deep neural netwo...
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Robust and Efficient Transfer Learning with HiddenParameter Markov Decision Processes
We introduce a new formulation of the Hidden Parameter Markov Decision P...
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Hybrid Code Networks: practical and efficient endtoend dialog control with supervised and reinforcement learning
Endtoend learning of recurrent neural networks (RNNs) is an attractive...
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Near Optimal Behavior via Approximate State Abstraction
The combinatorial explosion that plagues planning and reinforcement lear...
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AgentAgnostic HumanintheLoop Reinforcement Learning
Providing Reinforcement Learning agents with expert advice can dramatica...
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Sampleefficient Deep Reinforcement Learning for Dialog Control
Representing a dialog policy as a recurrent neural network (RNN) is attr...
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The Surfacing of Multiview 3D Drawings via Lofting and Occlusion Reasoning
The threedimensional reconstruction of scenes from multiple views has m...
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Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes
Due to physiological variation, patients diagnosed with the same conditi...
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Parametric Gaussian Process Regression for Big Data
This work introduces the concept of parametric Gaussian processes (PGPs)...
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Brown University
Brown University is a private Ivy League research university in Providence, Rhode Island, United States.