probability density

Density estimation with LLMs: a geometric investigation of in-context learning trajectories ICLR 2025 Probability-Density-aware Semi-supervised Learning AAAI 2025 Probability Density Geodesics in Image Diffusion Latent Space CVPR 2025 A Score-Based Deterministic Diffusion Algorithm with Smooth Scores for General Distributions AAAI 2024 A Kernel Stein Test of Goodness of Fit for Sequential Models ICML 2023 Canonical normalizing flows for manifold learning NeurIPS 2023 Density estimation on low-dimensional manifolds: an inflation-deflation approach JMLR 2023 GANs as Gradient Flows that Converge JMLR 2023 Quantitative Universal Approximation Bounds for Deep Belief Networks ICML 2023 Transfer Knowledge From Head to Tail: Uncertainty Calibration Under Long-Tailed Distribution CVPR 2023 Convergence for score-based generative modeling with polynomial complexity NeurIPS 2022 Generative Flows With Invertible Attentions CVPR 2022 Hiding Images in Deep Probabilistic Models NeurIPS 2022 Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows ICML 2022 Improving the Expressiveness of Neural Vocoding with Non-Affine Normalizing Flows Interspeech 2021 Large-Scale Wasserstein Gradient Flows NeurIPS 2021 The Base Measure Problem and its Solution AISTATS 2021 Difference-Seeking Generative Adversarial Network--Unseen Sample Generation ICLR 2020 Hierarchical nucleation in deep neural networks NeurIPS 2020 A minimax near-optimal algorithm for adaptive rejection sampling ALT 2019 Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams JMLR 2019 Deep Density Destructors ICML 2018 Embedding Words as Distributions with a Bayesian Skip-gram Model COLING 2018 Mode-Seeking Clustering and Density Ridge Estimation via Direct Estimation of Density-Derivative-Ratios JMLR 2018 Group-Wise Point-Set Registration Based on Renyi's Second Order Entropy CVPR 2017