Omead Pooladzandi

According to our database, Omead Pooladzandi authored at least 12 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Diverse Imitation Learning via Self-Organizing Generative Models.

Arash Vahabpour, Tianyi Wang, Qiujing Lu, Omead Pooladzandi, Vwani Roychowdhury

IEEE Trans. Neural Networks Learn. Syst., April, 2025

2024

PureEBM: Universal Poison Purification via Mid-Run Dynamics of Energy-Based Models.

Omead Pooladzandi, Jeffrey Jiang, Sunay Bhat, Gregory J. Pottie

CoRR, 2024

Curvature-Informed SGD via General Purpose Lie-Group Preconditioners.

Omead Pooladzandi, Xilin Li

CoRR, 2024

PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics.

Omead Pooladzandi, Sunay Bhat, Jeffrey Jiang, Alexander Branch, Gregory J. Pottie

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Fast Training of Generalizable Deep Neural Networks

Omead Pooladzandi

PhD thesis, 2023

Towards Composable Distributions of Latent Space Augmentations.

Omead Pooladzandi, Jeffrey Jiang, Sunay Bhat, Gregory J. Pottie

CoRR, 2023

Generating High Fidelity Synthetic Data via Coreset selection and Entropic Regularization.

Omead Pooladzandi, Pasha Khosravi, Erik Nijkamp, Baharan Mirzasoleiman

CoRR, 2023

Exploring the Potential of VAE Decoders for Enhanced Speech Re-Synthesis.

Omead Pooladzandi, Xilin Li, Yang Gao, Lalin Theverapperuma

Proceedings of the IEEE Statistical Signal Processing Workshop, 2023

2022

Improving Levenberg-Marquardt Algorithm for Neural Networks.

Omead Pooladzandi, Yiming Zhou

CoRR, 2022

Hypothesis Testing using Causal and Causal Variational Generative Models.

Jeffrey Jiang, Omead Pooladzandi, Sunay Bhat, Gregory J. Pottie

CoRR, 2022

De-Biasing Generative Models using Counterfactual Methods.

Sunay Bhat, Jeffrey Jiang, Omead Pooladzandi, Gregory J. Pottie

CoRR, 2022

Adaptive Second Order Coresets for Data-efficient Machine Learning.

Omead Pooladzandi, David Davini, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2022