categorical distribution

Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics ICML 2025 Evidential Knowledge Distillation ICCV 2025 Smooth Interpolation for Improved Discrete Graph Generative Models ICML 2025 Categorical Flow Matching on Statistical Manifolds NeurIPS 2024 DMTG: One-Shot Differentiable Multi-Task Grouping ICML 2024 How to Trade Off the Quantity and Capacity of Teacher Ensemble: Learning Categorical Distribution to Stochastically Employ a Teacher for Distillation AAAI 2024 Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model NeurIPS 2024 Predicting Label Distribution from Ternary Labels NeurIPS 2024 Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data ICML 2024 Class Overwhelms: Mutual Conditional Blended-Target Domain Adaptation AAAI 2023 Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick NeurIPS 2023 Diffusing Gaussian Mixtures for Generating Categorical Data AAAI 2023 AdaCat: Adaptive categorical discretization for autoregressive models UAI 2022 First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data NeurIPS 2022 Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions NeurIPS 2021 Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement ICML 2019 An Analysis of Categorical Distributional Reinforcement Learning AISTATS 2018 Augment and Reduce: Stochastic Inference for Large Categorical Distributions ICML 2018 Goodness-of-Fit Tests for Random Partitions via Symmetric Polynomials JMLR 2018 Bayesian Aggregation of Categorical Distributions with Applications in Crowdsourcing IJCAI 2017 The power of absolute discounting: all-dimensional distribution estimation NeurIPS 2017