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Variational Inference

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TitleStatusHype
Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithmCode1
Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks—0
A Non-negative VAE:the Generalized Gamma Belief Network—0
Distance-Preserving Spatial Representations in Genomic Data—0
Alpha-VI DeepONet: A prior-robust variational Bayesian approach for enhancing DeepONets with uncertainty quantification—0
Graph Representation Learning via Causal Diffusion for Out-of-Distribution RecommendationCode1
Weak neural variational inference for solving Bayesian inverse problems without forward models: applications in elastographyCode0
Variational Inference Using Material Point Method—0
Regularized Multi-Decoder Ensemble for an Error-Aware Scene Representation Network—0
Amortized Posterior Sampling with Diffusion Prior Distillation—0
Gradient-based inference of abstract task representations for generalization in neural networks—0
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational InferenceCode0
Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes—0
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
Neural information field filter—0
Revisiting Score Function Estimators for k-Subset Sampling—0
SoftCVI: Contrastive variational inference with self-generated soft labelsCode0
Hyperspectral Unmixing Under Endmember Variability: A Variational Inference Framework—0
Improving Graph Out-of-distribution Generalization on Real-world Data—0
Variational Inference via Smoothed Particle Hydrodynamics—0
Autoregressive Speech Synthesis without Vector Quantization—0
Variational Best-of-N Alignment—0
Idiographic Personality Gaussian Process for Psychological Assessment—0
Scalable Variational Causal Discovery Unconstrained by AcyclicityCode0
Randomized Physics-Informed Neural Networks for Bayesian Data AssimilationCode1
Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-ShiftsCode0
Neural Probabilistic Logic Learning for Knowledge Graph Reasoning—0
Scalable Multi-Output Gaussian Processes with Stochastic Variational Inference—0
Adaptive RKHS Fourier Features for Compositional Gaussian Process ModelsCode0
Particle Semi-Implicit Variational InferenceCode0
Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models—0
Time Series Clustering with General State Space Models via Stochastic Variational InferenceCode0
Amplify Graph Learning for Recommendation via Sparsity Completion—0
Torchtree: flexible phylogenetic model development and inference using PyTorchCode1
Learning Optimal Filters Using Variational Inference—0
Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference—0
Tree-based variational inference for Poisson log-normal modelsCode0
What type of inference is planning?Code0
CausalMMM: Learning Causal Structure for Marketing Mix Modeling—0
VICatMix: variational Bayesian clustering and variable selection for discrete biomedical dataCode0
Flexible Tails for Normalizing FlowsCode0
Probabilistic Programming with Programmable Variational Inference—0
Video Generation with Learned Action Prior—0
Variational Distillation of Diffusion Policies into Mixture of Experts—0
Period Singer: Integrating Periodic and Aperiodic Variational Autoencoders for Natural-Sounding End-to-End Singing Voice Synthesis—0
Injective flows for star-like manifolds—0
Assessment of Uncertainty Quantification in Universal Differential Equations—0
Efficient Mixture Learning in Black-Box Variational InferenceCode0
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for SamplingCode1
Convergence rate of random scan Coordinate Ascent Variational Inference under log-concavity—0
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