kernel density estimation

Adaptive Clustering Using Kernel Density Estimators JMLR 2023 Better Correlation and Robustness: A Distribution-Balanced Self-Supervised Learning Framework for Automatic Dialogue Evaluation NeurIPS 2023 CoDrug: Conformal Drug Property Prediction with Density Estimation under Covariate Shift NeurIPS 2023 Dimensionality Reduction for General KDE Mode Finding ICML 2023 Fast Approximation of Similarity Graphs with Kernel Density Estimation NeurIPS 2023 Fast Private Kernel Density Estimation via Locality Sensitive Quantization ICML 2023 KDEformer: Accelerating Transformers via Kernel Density Estimation ICML 2023 Robust Algorithms on Adaptive Inputs from Bounded Adversaries ICLR 2023 RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data ICLR 2023 Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation ICLR 2023 Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks ICLR 2023 UEQMS: UMAP Embedded Quick Mean Shift Algorithm for High Dimensional Clustering AAAI 2023 Variational Weighting for Kernel Density Ratios NeurIPS 2023 A Computable Definition of the Spectral Bias AAAI 2022 Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff AISTATS 2022 DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search AISTATS 2022 Meta Reinforcement Learning with Finite Training Tasks - a Density Estimation Approach NeurIPS 2022 Metrics of Calibration for Probabilistic Predictions JMLR 2022 Point Cloud Generation with Continuous Conditioning AISTATS 2022 Point Density-Aware Voxels for LiDAR 3D Object Detection CVPR 2022 Robust Kernel Density Estimation with Median-of-Means principle ICML 2022 The Correlation-assisted Missing Data Estimator JMLR 2022 A sampling-based circuit for optimal decision making NeurIPS 2021 Density of States Estimation for Out of Distribution Detection AISTATS 2021 Instance-Conditioned GAN NeurIPS 2021