| Distributed MCMC Inference in Dirichlet Process Mixture Models Using Julia O Dinari, A Yu, O Freifeld, JW Fisher III CCGrid HPML Workshop, 2019 | 17 | 2019 |
| Revisiting dp-means: fast scalable algorithms via parallelism and delayed cluster creation O Dinari, O Freifeld Uncertainty in Artificial Intelligence, 579-588, 2022 | 6 | 2022 |
| Variational-and metric-based deep latent space for out-of-distribution detection O Dinari, O Freifeld The 38th Conference on Uncertainty in Artificial Intelligence, 2022 | 5 | 2022 |
| Sampling in Dirichlet Process Mixture Models for Clustering Streaming Data O Dinari, O Freifeld International Conference on Artificial Intelligence and Statistics, 818-835, 2022 | 5 | 2022 |
| Scalable and Flexible Clustering of Grouped Data via Parallel and Distributed Sampling in Versatile Hierarchical Dirichlet Processes O Dinari, O Freifeld Conference on Uncertainty in Artificial Intelligence, 231-240, 2020 | 2 | 2020 |
| Common Failure Modes of Subcluster-based Sampling in Dirichlet Process Gaussian Mixture Models and a Deep-learning Solution. V Winter, O Dinari, O Freifeld AISTATS, 2022 | 1 | 2022 |
| From ViT Features to Training-free Video Object Segmentation via Streaming-data Mixture Models R Uziel, O Dinari, O Freifeld Advances in Neural Information Processing Systems 36, 10995-11007, 2023 | | 2023 |
| CPU-and GPU-based Distributed Sampling in Dirichlet Process Mixtures for Large-scale Analysis O Dinari, R Zamir, JW Fisher III, O Freifeld arXiv preprint arXiv:2204.08988, 2022 | | 2022 |
| Variational-and Metric-based Deep Latent Space for Out-of-Distribution Detection–Supplementary Material O Dinari, O Freifeld | | |
Oren FreifeldBen-Gurion UniversityE-mailová adresa ověřena na: cs.bgu.ac.il
