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Variational Inference

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Showing 1901–1950 of 2274 papers

TitleStatusHype
Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep LearningCode0
Particle-based Energetic Variational InferenceCode0
Generating Neural Networks with Neural NetworksCode0
Generative Adversarial Networks with Decoder-Encoder Output NoiseCode0
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial SettingsCode0
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw DataCode0
Deep Recurrent Generative Decoder for Abstractive Text SummarizationCode0
VIFS: An End-to-End Variational Inference for Foley Sound SynthesisCode0
Augment and Reduce: Stochastic Inference for Large Categorical DistributionsCode0
Particle Semi-Implicit Variational InferenceCode0
Deep Recurrent Gaussian Process with Variational Sparse Spectrum ApproximationCode0
Partitioned Variational Inference: A Framework for Probabilistic Federated LearningCode0
Generative Topic Embedding: a Continuous Representation of Documents (Extended Version with Proofs)Code0
Variational inference for the multi-armed contextual banditCode0
Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in IndiaCode0
Learning Waveform-Based Acoustic Models using Deep Variational Convolutional Neural NetworksCode0
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective InferenceCode0
GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree TopologiesCode0
Deep Markov Spatio-Temporal FactorizationCode0
GFlowNets and variational inferenceCode0
A Compact Representation for Bayesian Neural Networks By Removing Permutation SymmetryCode0
On the Expressiveness of Approximate Inference in Bayesian Neural NetworksCode0
Globally Convergent Variational InferenceCode0
Augment and Reduce: Stochastic Inference for Large Categorical DistributionsCode0
Bridging the Gap Between Variational Inference and Wasserstein Gradient FlowsCode0
Deep Generative Modeling for Identification of Noisy, Non-Stationary Dynamical SystemsCode0
Pathwise Derivatives Beyond the Reparameterization TrickCode0
Z-Forcing: Training Stochastic Recurrent NetworksCode0
Gradient-based optimization for variational empirical Bayes multiple regressionCode0
Gradient-Based Quantification of Epistemic Uncertainty for Deep Object DetectorsCode0
Deep Gaussian Processes with Importance-Weighted Variational InferenceCode0
Deep Gaussian Processes for Multi-fidelity ModelingCode0
Deep Gaussian Processes for Air Quality InferenceCode0
Learning to infer in recurrent biological networksCode0
Variational Latent Branching Model for Off-Policy EvaluationCode0
Unbiased Implicit Variational InferenceCode0
GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic ModelCode0
Graphite: Iterative Generative Modeling of GraphsCode0
Uncertainty-Aware Attention for Reliable Interpretation and PredictionCode0
Deep Gaussian Markov Random FieldsCode0
Advancing calibration for stochastic agent-based models in epidemiology with Stein variational inference and Gaussian process surrogatesCode0
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation MatrixCode0
Uncertainty-based Continual Learning with Adaptive RegularizationCode0
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and UtilityCode0
A Theoretically Grounded Application of Dropout in Recurrent Neural NetworksCode0
Stable Training of Normalizing Flows for High-dimensional Variational InferenceCode0
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal PosteriorsCode0
Hamiltonian Variational Auto-EncoderCode0
Handling the Positive-Definite Constraint in the Bayesian Learning RuleCode0
Harnessing Out-Of-Distribution Examples via Augmenting Content and StyleCode0
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