variational inference

Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds AISTATS 2024 Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling ICML 2024 Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification ICLR 2024 Building Expressive and Tractable Probabilistic Generative Models: A Review IJCAI 2024 Cauchy-Schwarz Divergence Information Bottleneck for Regression ICLR 2024 Causal Discovery Inspired Unsupervised Domain Adaptation for Emotion-Cause Pair Extraction EMNLP 2024 CLAP: Collaborative Adaptation for Patchwork Learning ICLR 2024 Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference NeurIPS 2024 Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting AAAI 2024 Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization ICML 2024 DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation NeurIPS 2024 Deep Unfolded Network with Intrinsic Supervision for Pan-Sharpening AAAI 2024 Deep Variational Incomplete Multi-View Clustering: Exploring Shared Clustering Structures AAAI 2024 Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization NeurIPS 2024 DiffusionDialog: A Diffusion Model for Diverse Dialog Generation with Latent Space COLING 2024 Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion NeurIPS 2024 Diffusion Models for Multi-Task Generative Modeling ICLR 2024 Diffusion Models With Learned Adaptive Noise NeurIPS 2024 Diffusion-NAT: Self-Prompting Discrete Diffusion for Non-Autoregressive Text Generation EACL 2024 Diffusion Priors for Variational Likelihood Estimation and Image Denoising NeurIPS 2024 Discovering Mixtures of Structural Causal Models from Time Series Data ICML 2024 Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference ICLR 2024 DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions EMNLP 2024 Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm NeurIPS 2024 Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling NeurIPS 2024