5 papers · 1 filter
Advances in Neural Controlled Differential Equations
Benjamin Walker
Many real-world systems evolve continuously, yet most machine learning models interpret time series as discrete sequences. Continuous-time approaches instead treat time series as s…
Universal Time Series Generation with Neural Controlled Differential Equations
Torben Berndt, Elyes Farjallah, Leif Seute +3
Recent work on the sequence universality of State Space Models (SSMs) has introduced efficient, maximally expressive continuous-time approaches for time-series modelling. While the…
Faithful Embeddings of Irregular and Asynchronous Data for Online Log-NCDEs
Benjamin Walker, Alexandre Bloch, Lingyi Yang +2
Continuous-time models are a natural choice for irregular and asynchronous data. A central design choice is how to embed discrete observations into continuous time. Interpolation-…
Chess-World-Model: A 10M-Game Benchmark for Exact State Tracking from Chess Move Sequences
Benjamin Walker, Terry Lyons
World models require state tracking, which is the ability to maintain a correct latent state across action sequences. Existing benchmarks are often synthetic or language-based, lim…
The Exponentially Weighted Signature
Alexandre Bloch, Samuel N. Cohen, Terry Lyons +2
The signature is a canonical representation of a multidimensional path over an interval. However, it treats all historical information uniformly, offering no intrinsic mechanism fo…