kullback-leibler divergence

Probabilistic Fusion of Neural Networks that Incorporates Global Information ACML 2022 Ranking Distance Calibration for Cross-Domain Few-Shot Learning CVPR 2022 Regularizing End-to-End Speech Translation with Triangular Decomposition Agreement AAAI 2022 Resampling Base Distributions of Normalizing Flows AISTATS 2022 Robust computation of optimal transport by $β$-potential regularization ACML 2022 Sampling with Mirrored Stein Operators ICLR 2022 Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance NeurIPS 2022 Sliced Wasserstein variational inference ACML 2022 A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning ICML 2021 An Alternative Probabilistic Interpretation of the Huber Loss CVPR 2021 An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives NeurIPS 2021 Challenging the Semi-Supervised VAE Framework for Text Classification EMNLP 2021 Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation IJCAI 2021 Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models NeurIPS 2021 Expanding Boundaries of Gap Safe Screening JMLR 2021 Fisher Auto-Encoders AISTATS 2021 Imitation with Neural Density Models NeurIPS 2021 Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence NeurIPS 2021 Measure Transport with Kernel Stein Discrepancy AISTATS 2021 Non-asymptotic Performance Guarantees for Neural Estimation of f-Divergences AISTATS 2021 On Robust Optimal Transport: Computational Complexity and Barycenter Computation NeurIPS 2021 On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness COLT 2021 On the Convex Combination of Determinantal Point Processes ACML 2021 On the Role of Data in PAC-Bayes Bounds AISTATS 2021 RaSE: Random Subspace Ensemble Classification JMLR 2021