
Implicit competitive regularization in GANs
Generative adversarial networks (GANs) are capable of producing high qua...
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OutofDistribution Detection Using Neural Rendering Generative Models
Outofdistribution (OoD) detection is a natural downstream task for dee...
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FERAtt: Facial Expression Recognition with Attention Net
We present a new endtoend network architecture for facial expression r...
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Learning Calibratable Policies using Programmatic StyleConsistency
We study the important and challenging problem of controllable generatio...
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Physicist's Journeys Through the AI World  A Topical Review. There is no royal road to unsupervised learning
Artificial Intelligence (AI), defined in its most simple form, is a tech...
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SLM Lab: A Comprehensive Benchmark and Modular Software Framework for Reproducible Deep Reinforcement Learning
We introduce SLM Lab, a software framework for reproducible reinforcemen...
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Plug and Play Language Models: a Simple Approach to Controlled Text Generation
Large transformerbased language models (LMs) trained on huge text corpo...
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A General Framework for Multifidelity Bayesian Optimization with Gaussian Processes
How can we efficiently gather information to optimize an unknown functio...
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A General Method for Amortizing Variational Filtering
We introduce the variational filtering EM algorithm, a simple, generalp...
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Deep Metric Structured Learning For Facial Expression Recognition
We propose a deep metric learning model to create embedded subspaces wi...
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RiskAverse Planning Under Uncertainty
We consider the problem of designing policies for partially observable M...
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HMMguided frame querying for bandwidthconstrained video search
We design an agent to search for frames of interest in video stored on a...
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Using Data Imputation for Signal Separation in High Contrast Imaging
To characterize circumstellar systems in high contrast imaging, the fund...
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Consistent Robust Adversarial Prediction for General Multiclass Classification
We propose a robust adversarial prediction framework for general multicl...
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A Stochastic Interpretation of Stochastic Mirror Descent: RiskSensitive Optimality
Stochastic mirror descent (SMD) is a fairly new family of algorithms tha...
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Recognition in Terra Incognita
It is desirable for detection and classification algorithms to generaliz...
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Analysis Of Momentum Methods
Gradient decentbased optimization methods underpin the parameter traini...
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Approximate Causal Abstraction
Scientific models describe natural phenomena at different levels of abst...
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Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions
We focus on the problem of predicting future states of entities in compl...
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Kernel Mode Decomposition and programmable/interpretable regression networks
Mode decomposition is a prototypical pattern recognition problem that ca...
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Open Vocabulary Learning on Source Code with a GraphStructured Cache
Machine learning models that take computer program source code as input ...
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ASPbased Discovery of SemiMarkovian Causal Models under Weaker Assumptions
In recent years the possibility of relaxing the socalled Faithfulness a...
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Robust Regression for Safe Exploration in Control
We study the problem of safe learning and exploration in sequential cont...
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Improving the Robustness of Deep Neural Networks via Stability Training
In this paper we address the issue of output instability of deep neural ...
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Quantifying Performance of Bipedal Standing with Multichannel EMG
Spinal cord stimulation has enabled humans with motor complete spinal co...
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A Parallelizable Acceleration Framework for Packing Linear Programs
This paper presents an acceleration framework for packing linear program...
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Meta Inverse Reinforcement Learning via Maximum Reward Sharing for Human Motion Analysis
This work handles the inverse reinforcement learning (IRL) problem where...
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Bayesian Optimization for Parameter Tuning of the XOR Neural Network
When applying Machine Learning techniques to problems, one must select m...
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SEGMENT3D: A Webbased Application for Collaborative Segmentation of 3D images used in the Shoot Apical Meristem
The quantitative analysis of 3D confocal microscopy images of the shoot ...
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Effective Image Differencing with ConvNets for Realtime Transient Hunting
Large sky surveys are increasingly relying on image subtraction pipeline...
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Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted HighResolution Simulations
Climate projections continue to be marred by large uncertainties, which ...
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DeepLearnt Classification of Light Curves
Astronomy light curves are sparse, gappy, and heteroscedastic. As a resu...
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On the enumeration of sentences by compactness
Presented is a Julia metaprogram that discovers compact theories from d...
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Diffusion Convolutional Recurrent Neural Network: DataDriven Traffic Forecasting
Spatiotemporal forecasting has various applications in neuroscience, cli...
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FixedRank Approximation of a PositiveSemidefinite Matrix from Streaming Data
Several important applications, such as streaming PCA and semidefinite p...
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What your Facebook Profile Picture Reveals about your Personality
People spend considerable effort managing the impressions they give othe...
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Genetic optimization of the Hyperloop route through the Grapevine
We demonstrate a genetic algorithm that employs a versatile fitness func...
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Clinical Patient Tracking in the Presence of Transient and Permanent Occlusions via Geodesic Feature
This paper develops a method to use RGBD cameras to track the motions o...
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Benchmarking and Error Diagnosis in MultiInstance Pose Estimation
We propose a new method to analyze the impact of errors in algorithms fo...
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Reinforcement Learning in RichObservation MDPs using Spectral Methods
Designing effective explorationexploitation algorithms in Markov decisi...
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Uncertainty Quantification in the Classification of High Dimensional Data
Classification of high dimensional data finds wideranging applications....
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PhaseMapper: An AI Platform to Accelerate High Throughput Materials Discovery
HighThroughput materials discovery involves the rapid synthesis, measur...
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Synthesis of Stochastic Flow Networks
A stochastic flow network is a directed graph with incoming edges (input...
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Parameter Selection Algorithm For Continuous Variables
In this article, we propose a new algorithm for supervised learning meth...
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A Matrix Factorization Approach for Learning SemidefiniteRepresentable Regularizers
Regularization techniques are widely employed in optimizationbased appr...
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Causal Discovery from Subsampled Time Series Data by Constraint Optimization
This paper focuses on causal structure estimation from time series data ...
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The Possibilities and Limitations of Private Prediction Markets
We consider the design of private prediction markets, financial markets ...
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Adaptive evolution on neutral networks
We study the evolution of large but finite asexual populations evolving ...
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Randomized singleview algorithms for lowrank matrix approximation
This paper develops a suite of algorithms for constructing lowrank appr...
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Gamblets for opening the complexitybottleneck of implicit schemes for hyperbolic and parabolic ODEs/PDEs with rough coefficients
Implicit schemes are popular methods for the integration of time depende...
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California Institute of Technology
The California Institute of Technology is a private doctorategranting research university located in Pasadena, California, United States.