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kullback-leibler divergence

181 papers

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Also known as

KL KL-DIVERGENCE KLD KL DIVERGENCE

Co-occurring keywords

variational inference (2069) kl divergence (196) generative model (2892) bayesian inference (1907) posterior distribution (259) probabilistic modeling (852) neural network (6616) knowledge distillation (3725) mutual information (724) variational autoencoder (1288)

Papers

An approximate KLD based experimental design for models with intractable likelihoods AISTATS 2020
Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models AISTATS 2020
An NMF-HMM Speech Enhancement Method Based on Kullback-Leibler Divergence INTERSPEECH 2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away ACL 2020
Distributionally Robust Parametric Maximum Likelihood Estimation NIPS 2020
Markovian Score Climbing: Variational Inference with KL(p||q) NIPS 2020
Variational Bayesian Unlearning NIPS 2020
Greedy inference with structure-exploiting lazy maps NIPS 2020
Posterior Re-calibration for Imbalanced Datasets NIPS 2020
Consistent recovery threshold of hidden nearest neighbor graphs COLT 2020
Experimenting with Power Divergences for Language Modeling EMNLP 2019
Investigation of Cost Function for Supervised Monaural Speech Separation INTERSPEECH 2019
Fisher Efficient Inference of Intractable Models NIPS 2019
Learning a Mixture of Granularity-Specific Experts for Fine-Grained Categorization ICCV 2019
A Theory of Regularized Markov Decision Processes ICML 2019
CLVSA: A Convolutional LSTM Based Variational Sequence-to-Sequence Model with Attention for Predicting Trends of Financial Markets IJCAI 2019
Probabilistic Multilevel Clustering via Composite Transportation Distance AISTATS 2019
Experimenting with Power Divergences for Language Modeling IJCNLP 2019
On the Importance of the Kullback-Leibler Divergence Term in Variational Autoencoders for Text Generation EMNLP 2019
Tree Sampling Divergence: An Information-Theoretic Metric for Hierarchical Graph Clustering IJCAI 2019
Parametric Manifold Learning of Gaussian Mixture Models IJCAI 2019
Speaker Adaptation for Attention-Based End-to-End Speech Recognition INTERSPEECH 2019
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization NIPS 2019
Gradient Information for Representation and Modeling NIPS 2019
Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation NIPS 2019