Lachlan E. MacDonald

According to our database, Lachlan E. MacDonald authored at least 16 papers between 2022 and 2026.

Collaborative distances:

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

2026

On the Convergence, Implicit Bias, and Edge of Stability of Gradient Descent in Deep Learning: Reviewing recent progress [Special Issue on the Mathematics of Deep Learning].

Hancheng Min, Lachlan Ewen MacDonald, René Vidal

IEEE Signal Process. Mag., May, 2026

Centre manifold theorem for maps along manifolds of fixed points.

Lachlan Ewen MacDonald

CoRR, April, 2026

2025

Convergence Rates for Gradient Descent on the Edge of Stability for Overparametrised Least Squares.

Lachlan E. MacDonald, Hancheng Min, Leandro Palma, Salma Tarmoun, Ziqing Xu, René Vidal

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Understanding the Learning Dynamics of LoRA: A Gradient Flow Perspective on Low-Rank Adaptation in Matrix Factorization.

Ziqing Xu, Hancheng Min, Lachlan Ewen MacDonald, Jinqi Luo, Salma Tarmoun, Enrique Mallada, René Vidal

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

D'OH: Decoder-Only Random Hypernetworks for Implicit Neural Representations.

Cameron Gordon, Lachlan E. MacDonald, Hemanth Saratchandran, Simon Lucey

Proceedings of the Computer Vision - ACCV 2024, 2024

2023

On progressive sharpening, flat minima and generalisation.

Lachlan Ewen MacDonald, Jack Valmadre, Simon Lucey

CoRR, 2023

On Quantizing Implicit Neural Representations.

Cameron Gordon, Shin-Fang Ch'ng, Lachlan E. MacDonald, Simon Lucey

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

On skip connections and normalisation layers in deep optimisation.

Lachlan E. MacDonald, Jack Valmadre, Hemanth Saratchandran, Simon Lucey

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

How much does Initialization Affect Generalization?

Sameera Ramasinghe, Lachlan Ewen MacDonald, Moshiur R. Farazi, Hemanth Saratchandran, Simon Lucey

Proceedings of the International Conference on Machine Learning, 2023

Curvature-Aware Training for Coordinate Networks.

Hemanth Saratchandran, Shin-Fang Ch'ng, Sameera Ramasinghe, Lachlan E. MacDonald, Simon Lucey

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Flow Supervision for Deformable NeRF.

Chaoyang Wang, Lachlan Ewen MacDonald, László A. Jeni, Simon Lucey

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

A global analysis of global optimisation.

Lachlan Ewen MacDonald, Hemanth Saratchandran, Jack Valmadre, Simon Lucey

CoRR, 2022

How You Start Matters for Generalization.

Sameera Ramasinghe, Lachlan E. MacDonald, Moshiur R. Farazi, Hemanth Saratchandran, Simon Lucey

CoRR, 2022

On Regularizing Coordinate-MLPs.

Sameera Ramasinghe, Lachlan E. MacDonald, Simon Lucey

CoRR, 2022

On the Frequency-bias of Coordinate-MLPs.

Sameera Ramasinghe, Lachlan E. MacDonald, Simon Lucey

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Enabling Equivariance for Arbitrary Lie Groups.

Lachlan E. MacDonald, Sameera Ramasinghe, Simon Lucey

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022