19 citations · 26 across the 13 of their papers we have counts for
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…
Extending SSMs with the Exponentially Weighted Signature
Alexandre Bloch, Samuel N. Cohen, Terry Lyons +3
We introduce the exponentially weighted signature (EWS), a continuous-time model that computes iterated integrals of a path, where each increment is weighted by the matrix exponent…