variational inference

Variational Language Concepts for Interpreting Foundation Language Models EMNLP 2024 Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting NeurIPS 2024 Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts ICML 2024 Variational Resampling AISTATS 2024 VI-OOD: A Unified Framework of Representation Learning for Textual Out-of-distribution Detection COLING 2024 VISA: Variational Inference with Sequential Sample-Average Approximations NeurIPS 2024 VSGT: Variational Spatial and Gaussian Temporal Graph Models for EEG-based Emotion Recognition IJCAI 2024 Wasserstein Proximal Coordinate Gradient Algorithms JMLR 2024 What type of inference is planning? NeurIPS 2024 WorDepth: Variational Language Prior for Monocular Depth Estimation CVPR 2024 Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference ICLR 2023 A Continuous-time Stochastic Gradient Descent Method for Continuous Data JMLR 2023 Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models NeurIPS 2023 Actually Sparse Variational Gaussian Processes AISTATS 2023 Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification AISTATS 2023 A decoder suffices for query-adaptive variational inference UAI 2023 A Fair Generative Model Using LeCam Divergence AAAI 2023 A Flexible Diffusion Model ICML 2023 A Heavy-Tailed Algebra for Probabilistic Programming NeurIPS 2023 A Latent-Variable Model for Intrinsic Probing AAAI 2023 Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics JMLR 2023 Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs NeurIPS 2023 An Eigenmodel for Dynamic Multilayer Networks JMLR 2023 An Empirical Bayes Framework for Open-Domain Dialogue Generation EMNLP 2023 An improved variational approximate posterior for the deep Wishart process UAI 2023