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Variational Inference

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Showing 1751–1800 of 2274 papers

TitleStatusHype
Discrete flow posteriors for variational inference in discrete dynamical systems—0
Discrete-Valued Neural Networks Using Variational Inference—0
Disease Trajectory Maps—0
Disentangled Representation Learning with Transmitted Information Bottleneck—0
Disentangled Skill Embeddings for Reinforcement Learning—0
Disentangling by Partitioning: A Representation Learning Framework for Multimodal Sensory Data—0
Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VI—0
Disentangling Space and Time in Video with Hierarchical Variational Auto-encoders—0
Distributed Bayesian Estimation in Sensor Networks: Consensus on Marginal Densities—0
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server—0
Distributed Multitask Reinforcement Learning with Quadratic Convergence—0
Distributed Variational Representation Learning—0
Distribution Matching in Variational Inference—0
Diversifying Reply Suggestions using a Matching-Conditional Variational Autoencoder—0
Diversity and Consistency: Exploring Visual Question-Answer Pair Generation—0
Diversity-Aware Sign Language Production through a Pose Encoding Variational Autoencoder—0
Diversity-Promoting Bayesian Learning of Latent Variable Models—0
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation—0
D-MFVI: Distributed Mean Field Variational Inference using Bregman ADMM—0
Domain-Invariant Feature Alignment Using Variational Inference For Partial Domain Adaptation—0
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse—0
Doubly Reparameterized Importance Weighted Structure Learning for Scene Graph Generation—0
Doubly Semi-Implicit Variational Inference—0
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables—0
DPGIIL: Dirichlet Process-Deep Generative Model-Integrated Incremental Learning for Clustering in Transmissibility-based Online Structural Anomaly Detection—0
Differentially private stochastic expectation propagation (DP-SEP)—0
DPVI: A Dynamic-Weight Particle-Based Variational Inference Framework—0
DPVIm: Differentially Private Variational Inference Improved—0
DropMax: Adaptive Stochastic Softmax—0
Dropout Sampling for Robust Object Detection in Open-Set Conditions—0
Dual Adversarial Auto-Encoders for Clustering—0
Dual Adversarial Variational Embedding for Robust Recommendation—0
Dual Latent Variable Model for Low-Resource Natural Language Generation in Dialogue Systems—0
Dynamical Deep Generative Latent Modeling of 3D Skeletal Motion—0
Dynamic Collaborative Filtering with Compound Poisson Factorization—0
Dynamic Poisson Factorization—0
DySurv: dynamic deep learning model for survival analysis with conditional variational inference—0
Early Gains Matter: A Case for Preferring Generative over Discriminative Crowdsourcing Models—0
Edge-Fog Computing-Enabled EEG Data Compression via Asymmetrical Variational Discrete Cosine Transform Network—0
Edge Partition Modulated Graph Convolutional Networks—0
Efficient Approximate Inference with Walsh-Hadamard Variational Inference—0
Efficient Continuous Relaxations for Dense CRF—0
Efficient Correlated Topic Modeling with Topic Embedding—0
Efficient EM-Variational Inference for Hawkes Process—0
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens—0
Efficient Language Modeling with Automatic Relevance Determination in Recurrent Neural Networks—0
Efficient non-conjugate Gaussian process factor models for spike count data using polynomial approximations—0
Efficient non-conjugate Gaussian process factor models for spike countdata using polynomial approximations—0
Efficient Online Inference for Bayesian Nonparametric Relational Models—0
Efficient Reinforcement Learning with Large Language Model Priors—0
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