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Variational Inference

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Showing 1–50 of 2274 papers

TitleStatusHype
BlackJAX: Composable Bayesian inference in JAXCode5
HierSpeech++: Bridging the Gap between Semantic and Acoustic Representation of Speech by Hierarchical Variational Inference for Zero-shot Speech SynthesisCode3
Cold Diffusion: Inverting Arbitrary Image Transforms Without NoiseCode3
Gaussian Processes for Big DataCode2
Modelling Non-Smooth Signals with Complex Spectral StructureCode2
Leveraging Instance Features for Label Aggregation in Programmatic Weak SupervisionCode2
normflows: A PyTorch Package for Normalizing FlowsCode2
PointFlow: 3D Point Cloud Generation with Continuous Normalizing FlowsCode2
Variational Bayesian Last LayersCode2
Scalable Gradients for Stochastic Differential EquationsCode2
Denoising Diffusion Restoration ModelsCode2
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic CoherenceCode2
Neural Posterior Estimation for Cataloging Astronomical Images with Spatially Varying Backgrounds and Point Spread FunctionsCode2
Cross-lingual Contextualized Topic Models with Zero-shot LearningCode2
GPflow: A Gaussian process library using TensorFlowCode2
Neural Markov Random Field for Stereo MatchingCode2
PITS: Variational Pitch Inference without Fundamental Frequency for End-to-End Pitch-controllable TTSCode2
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information BudgetCode2
Batch and match: black-box variational inference with a score-based divergenceCode2
Tutorial on amortized optimizationCode2
Stable Derivative Free Gaussian Mixture Variational Inference for Bayesian Inverse ProblemsCode2
Can Transformers Learn Full Bayesian Inference in Context?Code1
Bidirectional Variational Inference for Non-Autoregressive Text-to-SpeechCode1
Categorical Normalizing Flows via Continuous TransformationsCode1
BCD Nets: Scalable Variational Approaches for Bayesian Causal DiscoveryCode1
Bayes-Newton Methods for Approximate Bayesian Inference with PSD GuaranteesCode1
Bit Allocation using OptimizationCode1
Adversarial AutoencodersCode1
Blind Equalization and Channel Estimation in Coherent Optical Communications Using Variational AutoencodersCode1
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for SamplingCode1
Bayesian sparsification for deep neural networks with Bayesian model reductionCode1
Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised SegmentationCode1
Bayesian Structure Learning with Generative Flow NetworksCode1
Beyond Opinion Mining: Summarizing Opinions of Customer ReviewsCode1
Cauchy-Schwarz Divergence Information Bottleneck for RegressionCode1
Bayesian Deep Learning for Remaining Useful Life Estimation via Stein Variational Gradient DescentCode1
BayesDAG: Gradient-Based Posterior Inference for Causal DiscoveryCode1
Bayesian Image Reconstruction using Deep Generative ModelsCode1
A Discrete Variational Recurrent Topic Model without the Reparametrization TrickCode1
A Differentiable Point Process with Its Application to Spiking Neural NetworksCode1
BaCaDI: Bayesian Causal Discovery with Unknown InterventionsCode1
Autoencoding Variational Inference For Topic ModelsCode1
BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuningCode1
BayesDLL: Bayesian Deep Learning LibraryCode1
Bayesian Confidence Calibration for Epistemic Uncertainty ModellingCode1
A Batch Normalized Inference Network Keeps the KL Vanishing AwayCode1
Bayesian neural networks via MCMC: a Python-based tutorialCode1
Accurate Node Feature Estimation with Structured Variational Graph AutoencoderCode1
Graph Representation Learning via Causal Diffusion for Out-of-Distribution RecommendationCode1
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