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kl divergence

195 papers

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Also known as

KULLBACK-LEIBLER KL

Co-occurring keywords

variational inference (2069) bayesian inference (1904) kullback-leibler divergence (179) language model (4573) variational autoencoder (1282) knowledge distillation (3680) large language model (12755) reinforcement learning (4122) markov chain monte carlo (724) mutual information (717)

Papers

Learning functions on multiple sets using multi-set transformers UAI 2022
USTC-NELSLIP at SemEval-2022 Task 11: Gazetteer-Adapted Integration Network for Multilingual Complex Named Entity Recognition SEMEVAL 2022
Variational Autoencoders: A Harmonic Perspective AISTATS 2022
USTC-NELSLIP at SemEval-2022 Task 11: Gazetteer-Adapted Integration Network for Multilingual Complex Named Entity Recognition NAACL 2022
Modeling Strong and Human-Like Gameplay with KL-Regularized Search ICML 2022
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent (Extended Abstract) IJCAI 2022
How Good Are Low-Rank Approximations in Gaussian Process Regression? AAAI 2022
Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement NIPS 2022
On Divergence Measures for Bayesian Pseudocoresets NIPS 2022
Integral Probability Metrics PAC-Bayes Bounds NIPS 2022
Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM NIPS 2022
Bayesian inference via sparse Hamiltonian flows NIPS 2022
QUARK: Controllable Text Generation with Reinforced Unlearning NIPS 2022
Uncertainty-aware Propagation Structure Reconstruction for Fake News Detection COLING 2022
Rate-Regularization and Generalization in Variational Autoencoders AISTATS 2021
Soft-IntroVAE: Analyzing and Improving the Introspective Variational Autoencoder CVPR 2021
Adaptive Curriculum Learning ICCV 2021
Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networks UAI 2021
Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets NIPS 2021
Longitudinal Variational Autoencoder AISTATS 2021
On the Importance of Gradients for Detecting Distributional Shifts in the Wild NIPS 2021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support NIPS 2021
On Robust Optimal Transport: Computational Complexity and Barycenter Computation NIPS 2021
R-Drop: Regularized Dropout for Neural Networks NIPS 2021
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent AISTATS 2021