From the 1 of 6 linked papers with an AI index.
6 papers
From Observation to Insight: Mechanistic World Models and the Quest for Autonomous Discovery
Ingmar Posner, Anson Lei, Bernhard Schölkopf
The paper introduces Mechanistic World Models, a framework that places reusable explanatory mechanisms at the core of AI systems to enable autonomous scientific discovery beyond me…
Imitation from Heterogeneous Demonstrations using Grounded Latent-Action World Models
Tianyou Wang, Anson Lei, Joe Watson +1
Imitation learning has emerged as a powerful paradigm for learning visuomotor policies, but its generalisation and stability are limited by the scale and quality of demonstration d…
Disentangling Dynamical Systems: Causal Representation Learning Meets Local Sparse Attention
Markus W. Baumgartner, Anson Lei, Joe Watson +1
Parametric system identification methods estimate the parameters of explicitly defined physical systems from data. Yet, they remain constrained by the need to provide an explicit f…
Intrinsically Interpretable Attention via Sparse Post-Training
Florent Draye, Anson Lei, Hsiao-Ru Pan +2
We introduce a simple post-training method that makes transformer attention sparse without sacrificing performance. Applying a flexible sparsity regularisation under a constrained-…
No Epoch Like the Present: Robust Climate Emulation Requires Out-of-Distribution Generalisation
Bradley Stanley-Clamp, Anson Lei, Hannah M. Christensen +1
Climate emulation is an out-of-distribution (OOD) projection task. This is precisely the challenge where modern Machine Learning (ML) methods are most prone to failure. Consequentl…
SPARTAN: A Sparse Transformer World Model Attending to What Matters
Anson Lei, Bernhard Schölkopf, Ingmar Posner
Capturing the interactions between entities in a structured way plays a central role in world models that flexibly adapt to changes in the environment. Recent works motivate the be…