variational inference

Joint Demosaicking and Denoising in the Wild: The Case of Training Under Ground Truth Uncertainty AAAI 2021 Joint Modeling of Visual Objects and Relations for Scene Graph Generation NeurIPS 2021 Kernel Continual Learning ICML 2021 Laplace Redux - Effortless Bayesian Deep Learning NeurIPS 2021 Latent Gaussian process with composite likelihoods and numerical quadrature AISTATS 2021 Latent Matters: Learning Deep State-Space Models NeurIPS 2021 Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification ICML 2021 Learning an Explicit Weighting Scheme for Adapting Complex HSI Noise CVPR 2021 Learning Causal Semantic Representation for Out-of-Distribution Prediction NeurIPS 2021 Learning Disentangled Behavior Embeddings NeurIPS 2021 Learning Dual Priors for JPEG Compression Artifacts Removal ICCV 2021 Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler AAAI 2021 Learning GPLVM with arbitrary kernels using the unscented transformation AISTATS 2021 Learning Latent Architectural Distribution in Differentiable Neural Architecture Search via Variational Information Maximization ICCV 2021 Learning Nonparametric Volterra Kernels with Gaussian Processes NeurIPS 2021 Learning Opinion Summarizers by Selecting Informative Reviews EMNLP 2021 Learning proposals for probabilistic programs with inference combinators UAI 2021 Learning Temporal Point Processes with Intermittent Observations AISTATS 2021 Learning to Learn Dense Gaussian Processes for Few-Shot Learning NeurIPS 2021 LiBRe: A Practical Bayesian Approach to Adversarial Detection CVPR 2021 Longitudinal Deep Kernel Gaussian Process Regression AAAI 2021 Marginalized Stochastic Natural Gradients for Black-Box Variational Inference ICML 2021 MARTA: Leveraging Human Rationales for Explainable Text Classification AAAI 2021 Matrix Product States for Inference in Discrete Probabilistic Models JMLR 2021 MCMC Variational Inference via Uncorrected Hamiltonian Annealing NeurIPS 2021