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Variational Inference

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Showing 1726–1750 of 2274 papers

TitleStatusHype
Deep Latent Force Models: ODE-based Process Convolutions for Bayesian Deep Learning—0
Deep Network Regularization via Bayesian Inference of Synaptic Connectivity—0
Deep Networks as Denoising Algorithms: Sample-Efficient Learning of Diffusion Models in High-Dimensional Graphical Models—0
Deep Operator Networks for Bayesian Parameter Estimation in PDEs—0
Deep Poisson Factorization Machines: factor analysis for mapping behaviors in journalist ecosystem—0
Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization—0
Fully probabilistic deep models for forward and inverse problems in parametric PDEs—0
Deep Probabilistic Models to Detect Data Poisoning Attacks—0
Deep Probabilistic Programming—0
Deep Probabilistic Video Compression—0
Deep Quantization: Encoding Convolutional Activations with Deep Generative Model—0
Deep Reinforcement Learning with Weighted Q-Learning—0
Deep State Space Models for Unconditional Word Generation—0
Deep Transformed Gaussian Processes—0
Deep Variational Inference Without Pixel-Wise Reconstruction—0
Dependency Grammar Induction with a Neural Variational Transition-based Parser—0
Deterministic Fokker-Planck Transport -- With Applications to Sampling, Variational Inference, Kernel Mean Embeddings & Sequential Monte Carlo—0
A Deterministic Approximation to Neural SDEs—0
D-GAN: Deep Generative Adversarial Nets for Spatio-Temporal Prediction—0
Differentiable Learning of Submodular Models—0
Differentially Private Continual Learning—0
DinTucker: Scaling up Gaussian process models on multidimensional arrays with billions of elements—0
Directed Variational Cross-encoder Network for Few-shot Multi-image Co-segmentation—0
Dirichlet process mixture models for non-stationary data streams—0
Discovering Latent Structural Causal Models from Spatio-Temporal Data—0
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