maximum likelihood

OverFlow: Putting flows on top of neural transducers for better TTS Interspeech 2023 Particle algorithms for maximum likelihood training of latent variable models AISTATS 2023 Provable benefits of score matching NeurIPS 2023 Statistical Efficiency of Score Matching: The View from Isoperimetry ICLR 2023 Training Energy-Based Normalizing Flow with Score-Matching Objectives NeurIPS 2023 Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation NeurIPS 2023 Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics AISTATS 2023 When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning NeurIPS 2023 ℓ_∞-Bounds of the MLE in the BTL Model under General Comparison Graphs UAI 2022 A Random Matrix Perspective on Random Tensors JMLR 2022 Are GANs overkill for NLP? NeurIPS 2022 A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model ICLR 2022 Beyond black box densities: Parameter learning for the deviated components NeurIPS 2022 BRIO: Bringing Order to Abstractive Summarization ACL 2022 Contrastive Learning with Expectation-Maximization for Weakly Supervised Phrase Grounding EMNLP 2022 Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation AAAI 2022 Convergence Rates for Gaussian Mixtures of Experts JMLR 2022 Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme ICLR 2022 Explaining Point Processes by Learning Interpretable Temporal Logic Rules ICLR 2022 Finite-Sample Maximum Likelihood Estimation of Location NeurIPS 2022 Generative Cooperative Networks for Natural Language Generation ICML 2022 Interval-censored Hawkes processes JMLR 2022 Keyphrase Generation via Soft and Hard Semantic Corrections EMNLP 2022 Learning Options via Compression NeurIPS 2022 Learning the Structure of Large Networked Systems Obeying Conservation Laws NeurIPS 2022