Bayesian & Probabilistic

Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification ICML 2021 Learning and testing junta distributions with sub cube conditioning COLT 2021 Learning an Explicit Weighting Scheme for Adapting Complex HSI Noise CVPR 2021 Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system L4DC 2021 Learning Bayesian Networks from Ordinal Data JMLR 2021 Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior AAAI 2021 Learning Deep Latent Variable Models by Short-Run MCMC Inference With Optimal Transport Correction CVPR 2021 Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent NeurIPS 2021 Learning Fast-Inference Bayesian Networks NeurIPS 2021 Learning Flexibly Distributional Representation for Low-quality 3D Face Recognition AAAI 2021 Learning Icosahedral Spherical Probability Map Based on Bingham Mixture Model for Vanishing Point Estimation ICCV 2021 Learning local modules in dynamic networks L4DC 2021 Learning Logic Rules for Document-Level Relation Extraction EMNLP 2021 Learning Nonparametric Volterra Kernels with Gaussian Processes NeurIPS 2021 Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes AISTATS 2021 Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression CVPR 2021 Learning Shared Subgraphs in Ising Model Pairs AISTATS 2021 Learning the Parameters of Bayesian Networks from Uncertain Data AAAI 2021 Learning to Learn Dense Gaussian Processes for Few-Shot Learning NeurIPS 2021 Learning to Sample from Censored Markov Random Fields COLT 2021 Lenient Regret and Good-Action Identification in Gaussian Process Bandits ICML 2021 Lifted reasoning meets weighted model integration UAI 2021 Light RUMs ICML 2021 Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models NeurIPS 2021 Local policy search with Bayesian optimization NeurIPS 2021