Variational Inference

SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder CVPR 2024 Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference AISTATS 2024 Soft Knowledge Prompt: Help External Knowledge Become a Better Teacher to Instruct LLM in Knowledge-based VQA ACL 2024 Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference ICML 2024 Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data ICLR 2024 Structured Probabilistic Coding AAAI 2024 StyleFlow: Disentangle Latent Representations via Normalizing Flow for Unsupervised Text Style Transfer COLING 2024 Symmetric Equilibrium Learning of VAEs AISTATS 2024 Task-Free Continual Generation and Representation Learning via Dynamic Expansionable Memory Cluster AAAI 2024 TFS-NeRF: Template-Free NeRF for Semantic 3D Reconstruction of Dynamic Scene NeurIPS 2024 The Star Geometry of Critic-Based Regularizer Learning NeurIPS 2024 Topic-VQ-VAE: Leveraging Latent Codebooks for Flexible Topic-Guided Document Generation AAAI 2024 Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach AISTATS 2024 Towards Practical Non-Adversarial Distribution Matching AISTATS 2024 Towards Understanding Future: Consistency Guided Probabilistic Modeling for Action Anticipation AAAI 2024 Towards Variable and Coordinated Holistic Co-Speech Motion Generation CVPR 2024 Training Bayesian Neural Networks with Sparse Subspace Variational Inference ICLR 2024 Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming NeurIPS 2024 Transport meets Variational Inference: Controlled Monte Carlo Diffusions ICLR 2024 TreeVI: Reparameterizable Tree-structured Variational Inference for Instance-level Correlation Capturing NeurIPS 2024 Understanding Likelihood of Normalizing Flow and Image Complexity through the Lens of Out-of-Distribution Detection AAAI 2024 Unified Generative Modeling of 3D Molecules with Bayesian Flow Networks ICLR 2024 Unity by Diversity: Improved Representation Learning for Multimodal VAEs NeurIPS 2024 Unrolled denoising networks provably learn to perform optimal Bayesian inference NeurIPS 2024 Unsupervised Hierarchical Topic Modeling via Anchor Word Clustering and Path Guidance EMNLP 2024