reparameterization trick

Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models ICLR 2025 Explicit Preference Optimization: No Need for an Implicit Reward Model ICML 2025 Neural Gaussian Similarity Modeling for Differential Graph Structure Learning AAAI 2024 pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction CVPR 2024 A Unified Knowledge Distillation Framework for Deep Directed Graphical Models CVPR 2023 Cell Variational Information Bottleneck Network ACML 2023 Cold Analysis of Rao-Blackwellized Straight-Through Gumbel-Softmax Gradient Estimator ICML 2023 Model-based Causal Bayesian Optimization ICLR 2023 BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuning ACML 2022 Transkimmer: Transformer Learns to Layer-wise Skim ACL 2022 Automatic Differentiation Variational Inference with Mixtures AISTATS 2021 End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series ICML 2021 Generalized Doubly Reparameterized Gradient Estimators ICML 2021 Posterior Promoted GAN With Distribution Discriminator for Unsupervised Image Synthesis CVPR 2021 Variational inference for nonlinear ordinary differential equations AISTATS 2021 Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems ICML 2020 Efficient Low Rank Gaussian Variational Inference for Neural Networks NeurIPS 2020 f-Divergence Variational Inference NeurIPS 2020 Generating Correct Answers for Progressive Matrices Intelligence Tests NeurIPS 2020 Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax NeurIPS 2020 Learning VAE-LDA Models with Rounded Reparameterization Trick EMNLP 2020 Relaxed Multivariate Bernoulli Distribution and Its Applications to Deep Generative Models UAI 2020 The continuous categorical: a novel simplex-valued exponential family ICML 2020 Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives ICLR 2019 GO Gradient for Expectation-Based Objectives ICLR 2019