importance sampling

OmniEdit: Building Image Editing Generalist Models Through Specialist Supervision ICLR 2025 RayFlow: Instance-Aware Diffusion Acceleration via Adaptive Flow Trajectories CVPR 2025 Revisiting Unbiased Implicit Variational Inference ICML 2025 Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs ACL 2025 TensoFlow: Tensorial Flow-based Sampler for Inverse Rendering CVPR 2025 Understanding the difficulties of posterior predictive estimation ICML 2025 Accelerating Neural Field Training via Soft Mining CVPR 2024 Adaptive importance sampling for heavy-tailed distributions via $α$-divergence minimization AISTATS 2024 Adversarial Likelihood Estimation With One-Way Flows WACV 2024 A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment JMLR 2024 Can Gaussian Sketching Converge Faster on a Preconditioned Landscape? ICML 2024 Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation Distillation AAAI 2024 Differentiable Distributionally Robust Optimization Layers ICML 2024 DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling AAAI 2024 Distributional Off-Policy Evaluation for Slate Recommendations AAAI 2024 Efficient Backpropagation with Variance Controlled Adaptive Sampling ICLR 2024 Error-aware Sampling in Adaptive Shells for Neural Surface Reconstruction IJCAI 2024 Estimating the Permanent by Nesting Importance Sampling ICML 2024 Exogenous Matching: Learning Good Proposals for Tractable Counterfactual Estimation NeurIPS 2024 Fast Reliability Estimation for Neural Networks with Adversarial Attack-Driven Importance Sampling UAI 2024 General bounds on the quality of Bayesian coresets NeurIPS 2024 GGD: Grafting Gradient Descent JMLR 2024 Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias AISTATS 2024 Implicit and Explicit Policy Constraints for Offline Reinforcement Learning CLeaR 2024 Importance Matching Lemma for Lossy Compression with Side Information AISTATS 2024