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Variational Inference

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TitleStatusHype
How particular is the physics of the free energy principle?—0
Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints—0
High Mutual Information in Representation Learning with Symmetric Variational Inference—0
Constraining the Dynamics of Deep Probabilistic Models—0
Improving Actor-Critic Reinforcement Learning via Hamiltonian Monte Carlo Method—0
Structured Dropout Variational Inference for Bayesian Neural Networks—0
Amortized Inference of Variational Bounds for Learning Noisy-OR—0
A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing—0
Spike-and-slab shrinkage priors for structurally sparse Bayesian neural networks—0
Higher-Order Inference for Multi-Class Log-Supermodular Models—0
Constrained Structure Learning for Scene Graph Generation—0
HierVST: Hierarchical Adaptive Zero-shot Voice Style Transfer—0
Constrained Stein Variational Gradient Descent for Robot Perception, Planning, and Identification—0
Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes—0
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations—0
Automated Variational Inference in Probabilistic Programming—0
Constrained Bayesian Inference for Low Rank Multitask Learning—0
Automated Variational Inference for Gaussian Process Models—0
Hierarchical Sparse Bayesian Multitask Model with Scalable Inference for Microbiome Analysis—0
Incorporating Group Prior into Variational Inference for Tail-User Behavior Modeling in CTR Prediction—0
Hierarchical models for neural population dynamics in the presence of non-stationarity—0
Incremental Variational Inference for Latent Dirichlet Allocation—0
Independent projections of diffusions: Gradient flows for variational inference and optimal mean field approximations—0
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations—0
Connection Discovery using Shared Images by Gaussian Relational Topic Model—0
Indian Buffet Process Deep Generative Models for Semi-Supervised Classification—0
Hierarchical mixtures of Unigram models for short text clustering: The role of Beta-Liouville priors—0
Inducing Interpretable Representations with Variational Autoencoders—0
Inference for determinantal point processes without spectral knowledge—0
Hierarchical Implicit Models and Likelihood-Free Variational Inference—0
Inferring the quantum density matrix with machine learning—0
Hierarchical Bayesian Personalized Recommendation: A Case Study and Beyond—0
Confidence Estimation via Sequential Likelihood Mixing—0
InfoNCE is variational inference in a recognition parameterised model—0
A Deterministic Global Optimization Method for Variational Inference—0
Information Field Theory and Artificial Intelligence—0
Information Theory with Kernel Methods—0
Informative Priors Improve the Reliability of Multimodal Clinical Data Classification—0
Injective flows for star-like manifolds—0
Input Dependent Sparse Gaussian Processes—0
Hierarchical Bayes Autoencoders—0
Refining Latent Representations: A Generative SSL Approach for Heterogeneous Graph Learning—0
Composing Normalizing Flows for Inverse Problems—0
Integrating Document Clustering and Topic Modeling—0
Amortized Context Vector Inference for Sequence-to-Sequence Networks—0
Variational Policy Propagation for Multi-agent Reinforcement Learning—0
Hamiltonian Policy Optimization in Reinforcement Learning—0
Interactive Graph Convolutional Filtering—0
Hamiltonian Policy Optimization—0
Half-VAE: An Encoder-Free VAE to Bypass Explicit Inverse Mapping—0
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