multimodal distribution

Leapfrog Diffusion Model for Stochastic Trajectory Prediction CVPR 2023 Can Push-forward Generative Models Fit Multimodal Distributions? NeurIPS 2022 CARD: Classification and Regression Diffusion Models NeurIPS 2022 Continuously Tempered PDMP samplers NeurIPS 2022 Joint 3D Object Detection and Tracking Using Spatio-Temporal Representation of Camera Image and LiDAR Point Clouds AAAI 2022 Revisiting Over-Smoothness in Text to Speech ACL 2022 Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models NeurIPS 2021 Likelihood-Based Diverse Sampling for Trajectory Forecasting ICCV 2021 Nested Variational Inference NeurIPS 2021 A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions NeurIPS 2020 Trust-Region Variational Inference with Gaussian Mixture Models JMLR 2020 Visual Relationship Detection with Low Rank Non-Negative Tensor Decomposition AAAI 2020 Hierarchical Optimal Transport for Multimodal Distribution Alignment NeurIPS 2019 Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction CoRL 2019 Leveraging exploration in off-policy algorithms via normalizing flows CoRL 2019 Modeling Personalization in Continuous Space for Response Generation via Augmented Wasserstein Autoencoders EMNLP 2019 Mode Normalization ICLR 2019 Pseudo-Extended Markov chain Monte Carlo NeurIPS 2019 RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection CVPR 2019 Accurate and Diverse Sampling of Sequences Based on a “Best of Many” Sample Objective CVPR 2018 Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo NeurIPS 2018 Efficient Gradient-Free Variational Inference using Policy Search ICML 2018 Mental Sampling in Multimodal Representations NeurIPS 2018 Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning NeurIPS 2018 Stochastic Gradient Monomial Gamma Sampler ICML 2017