Generalized Variational Continual Learning. - Noel Loo; Siddharth Swaroop; Richard E. Turner (ICLR, 2021)

Evolution of Neural Tangent Kernels under Benign and Adversarial Training. - Noel Loo; Ramin M. Hasani; Alexander Amini; Daniela Rus (NeurIPS, 2022)

Efficient Dataset Distillation using Random Feature Approximation. - Noel Loo; Ramin M. Hasani; Alexander Amini; Daniela Rus (NeurIPS, 2022)

Dataset Distillation with Convexified Implicit Gradients. - Noel Loo; Ramin M. Hasani; Mathias Lechner; Daniela Rus (ICML, 2023)

On the Size and Approximation Error of Distilled Datasets. - Alaa Maalouf; Murad Tukan; Noel Loo; Ramin M. Hasani; Mathias Lechner; Daniela Rus (NeurIPS, 2023)

Dataset Distillation Fixes Dataset Reconstruction Attacks. - Noel Loo; Ramin M. Hasani; Mathias Lechner; Daniela Rus (CoRR, 2023)

On the Size and Approximation Error of Distilled Sets. - Alaa Maalouf; Murad Tukan; Noel Loo; Ramin M. Hasani; Mathias Lechner; Daniela Rus (CoRR, 2023)

Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation. - Noel Loo; Ramin M. Hasani; Mathias Lechner; Alexander Amini; Daniela Rus (ICLR, 2024)

Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control. - Neehal Tumma; Mathias Lechner; Noel Loo; Ramin M. Hasani; Daniela Rus (ICLR, 2024)

Large Scale Dataset Distillation with Domain Shift. - Noel Loo; Alaa Maalouf; Ramin M. Hasani; Mathias Lechner; Alexander Amini; Daniela Rus (ICML, 2024)

Linear Projections of Teacher Embeddings for Few-Class Distillation. - Noel Loo; Fotis Iliopoulos; Wei Hu; Erik Vee (CoRR, 2024)