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Variational Inference

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Showing 76–100 of 2274 papers

TitleStatusHype
Neural Posterior Estimation for Cataloging Astronomical Images with Spatially Varying Backgrounds and Point Spread FunctionsCode2
Training Robust Graph Neural Networks by Modeling Noise DependenciesCode0
Advancing calibration for stochastic agent-based models in epidemiology with Stein variational inference and Gaussian process surrogatesCode0
Actively Inferring Optimal Measurement Sequences—0
Time Series Domain Adaptation via Latent Invariant Causal MechanismCode0
Logit Disagreement: OoD Detection with Bayesian Neural Networks—0
Safe Beyond the Horizon: Efficient Sampling-based MPC with Neural Control Barrier Functions—0
Confidence Estimation via Sequential Likelihood Mixing—0
Partially Observable Gaussian Process Network and Doubly Stochastic Variational Inference—0
Federated Variational Inference for Bayesian Mixture Models—0
Using the Path of Least Resistance to Explain Deep NetworksCode0
Simplify RLHF as Reward-Weighted SFT: A Variational Method—0
Censor Dependent Variational InferenceCode0
Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics—0
Quantification of model error for inverse problems in the Weak Neural Variational Inference framework—0
Functional Complexity-adaptive Temporal Tensor Decomposition—0
Koopman-Equivariant Gaussian Processes—0
The Odyssey of the Fittest: Can Agents Survive and Still Be Good?Code0
Variational Control for Guidance in Diffusion ModelsCode1
Bridging the inference gap in Mutimodal Variational Autoencoders—0
Mixture of neural operator experts for learning boundary conditions and model selection—0
Hierarchical Sparse Bayesian Multitask Model with Scalable Inference for Microbiome Analysis—0
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework—0
A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization—0
ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks—0
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