
Multilabel Contrastive Predictive Coding
Variational mutual information (MI) estimators are widely used in unsupe...
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Belief Propagation Neural Networks
Learned neural solvers have successfully been used to solve combinatoria...
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Experience Replay with Likelihoodfree Importance Weights
The use of past experiences to accelerate temporal difference (TD) learn...
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Robust and Onthefly Dataset Denoising for Image Classification
Memorization in overparameterized neural networks could severely hurt g...
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Training Deep EnergyBased Models with fDivergence Minimization
Deep energybased models (EBMs) are very flexible in distribution parame...
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Gaussianization Flows
Iterative Gaussianization is a fixedpoint iteration procedure that can ...
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Permutation Invariant Graph Generation via ScoreBased Generative Modeling
Learning generative models for graphstructured data is challenging beca...
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A Theory of Usable Information Under Computational Constraints
We propose a new framework for reasoning about information in complex sy...
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Bridging the Gap Between fGANs and Wasserstein GANs
Generative adversarial networks (GANs) have enjoyed much success in lear...
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Unsupervised OutofDistribution Detection with Batch Normalization
Likelihood from a generative model is a natural statistic for detecting ...
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Understanding the Limitations of Variational Mutual Information Estimators
Variational approaches based on neural networks are showing promise for ...
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Cross Domain Imitation Learning
We study the question of how to imitate tasks across domains with discre...
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MultiAgent Adversarial Inverse Reinforcement Learning
Reinforcement learning agents are prone to undesired behaviors due to re...
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Bias Correction of Learned Generative Models using LikelihoodFree Importance Weighting
A learned generative model often produces biased statistics relative to ...
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Calibrated ModelBased Deep Reinforcement Learning
Estimates of predictive uncertainty are important for accurate modelbas...
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Learning Controllable Fair Representations
Learning data representations that are transferable and fair with respec...
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Bias and Generalization in Deep Generative Models: An Empirical Study
In high dimensional settings, density estimation algorithms rely crucial...
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MultiAgent Generative Adversarial Imitation Learning
Imitation learning algorithms can be used to learn a policy from expert ...
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gSMat: A Scalable Sparse Matrixbased Join for SPARQL Query Processing
Resource Description Framework (RDF) has been widely used to represent i...
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The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models
A variety of learning objectives have been proposed for training latent ...
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Adversarial Constraint Learning for Structured Prediction
Constraintbased learning reduces the burden of collecting labels by hav...
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An Empirical Analysis of Proximal Policy Optimization with Kroneckerfactored Natural Gradients
In this technical report, we consider an approach that combines the PPO ...
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ANICEMC: Adversarial Training for MCMC
Existing Markov Chain Monte Carlo (MCMC) methods are either based on gen...
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InfoVAE: Information Maximizing Variational Autoencoders
It has been previously observed that variational autoencoders tend to ig...
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InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations
The goal of imitation learning is to mimic expert behavior without acces...
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On the Limits of Learning Representations with LabelBased Supervision
Advances in neural network based classifiers have transformed automatic ...
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Towards Deeper Understanding of Variational Autoencoding Models
We propose a new family of optimization criteria for variational autoen...
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Learning Hierarchical Features from Generative Models
Deep neural networks have been shown to be very successful at learning f...
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Factored Temporal Sigmoid Belief Networks for Sequence Learning
Deep conditional generative models are developed to simultaneously learn...
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MaxMargin Nonparametric Latent Feature Models for Link Prediction
Link prediction is a fundamental task in statistical network analysis. R...
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Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation
We present a discriminative nonparametric latent feature relational mode...
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Jiaming Song
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