Bayesian & Probabilistic

Directed Probabilistic Watershed NeurIPS 2021 Disentangling Generative Factors in Natural Language with Discrete Variational Autoencoders EMNLP 2021 Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning AISTATS 2021 Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference IJCAI 2021 Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series AAAI 2021 Efficient Bayesian Network Structure Learning via Parameterized Local Search on Topological Orderings AAAI 2021 Efficient Generative Modelling of Protein Structure Fragments using a Deep Markov Model ICML 2021 Efficient Sampling of Dependency Structure EMNLP 2021 Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes ICML 2021 Estimating High Order Gradients of the Data Distribution by Denoising NeurIPS 2021 Estimating the Unique Information of Continuous Variables NeurIPS 2021 Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte Carlo ICML 2021 Event and Entity Coreference using Trees to Encode Uncertainty in Joint Decisions EMNLP 2021 Evolution Strategies for Approximate Solution of Bayesian Games AAAI 2021 Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms NeurIPS 2021 Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach AAAI 2021 Exploiting a Zoo of Checkpoints for Unseen Tasks NeurIPS 2021 Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions NeurIPS 2021 Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics ICML 2021 Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification CVPR 2021 Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation NeurIPS 2021 Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds NeurIPS 2021 Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling UAI 2021 Fitting summary statistics of neural data with a differentiable spiking network simulator NeurIPS 2021 Flow-Based Kernel Prior With Application to Blind Super-Resolution CVPR 2021