Bayesian & Probabilistic

Reproducing kernel Hilbert C*-module and kernel mean embeddings JMLR 2021 Responsibility Attribution in Parameterized Markovian Models AAAI 2021 Reward Identification in Inverse Reinforcement Learning ICML 2021 RollingLDA: An Update Algorithm of Latent Dirichlet Allocation to Construct Consistent Time Series from Textual Data EMNLP 2021 Row-clustering of a Point Process-valued Matrix NeurIPS 2021 Sampling with Trusthworthy Constraints: A Variational Gradient Framework NeurIPS 2021 Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network ICML 2021 Scalable Bayesian Inverse Reinforcement Learning ICLR 2021 Scalable gradient matching based on state space Gaussian Processes ACML 2021 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes ICLR 2021 Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition ICML 2021 Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification NeurIPS 2021 Self-Conditioned Probabilistic Learning of Video Rescaling ICCV 2021 Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization AAAI 2021 SGA: A Robust Algorithm for Partial Recovery of Tree-Structured Graphical Models with Noisy Samples ICML 2021 SG-PALM: a Fast Physically Interpretable Tensor Graphical Model ICML 2021 SHPOS: A Theoretical Guaranteed Accelerated Particle Optimization Sampling Method IJCAI 2021 SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data ICML 2021 Simple and Effective VAE Training with Calibrated Decoders ICML 2021 Sinusoidal Flow: A Fast Invertible Autoregressive Flow ACML 2021 Skew-symmetrically perturbed gradient flow for convex optimization ACML 2021 Slice Sampling Reparameterization Gradients NeurIPS 2021 Soft Tensor Regression JMLR 2021 Source Identification for Mixtures of Product Distributions COLT 2021 Sparse within Sparse Gaussian Processes using Neighbor Information ICML 2021