18 papers
Learning from Local Walks on Dynamic Graphs with Bandit Feedback
Sourav Chakraborty, Amit Kiran Rege, Claire Monteleoni +1
We study stochastic multi-armed bandits on dynamic graphs, where arms correspond to the vertices of a network with time-varying edges. In this setting, the learner is restricted to…
Evaluating Skill and Stability of ArchesWeather and ArchesWeatherGen under Multi-Decadal Climate Simulations
Renu Singh, Robert Brunstein, Antonia Jost +5
We evaluate the climate simulation capabilities of ArchesWeather and ArchesWeatherGen, two machine learning models originally trained for weather forecasting and evaluated up to a…
ArchesClimate: Probabilistic Decadal Ensemble Generation With Flow Matching
Graham Clyne, Guillaume Couairon, Guillaume Gastineau +2
Internal variability is a dominant contributor to the uncertainty of predictions at the interannual to decadal timescale. A typical approach to separating the internal variability…
MotifGen: Spatiotemporal interpolation of misaligned satellite images via multi-source generative modeling, in an application to tropical cyclones
Clément Dauvilliers, Claire Monteleoni
Microwave satellite imagery plays a crucial role in monitoring tropical cyclone precipitation and intensity worldwide, but suffers from long revisit times, potentially missing rapi…
Flickering Multi-Armed Bandits
Sourav Chakraborty, Amit Kiran Rege, Claire Monteleoni +1
We introduce Flickering Multi-Armed Bandits (FMAB) to model sequential decision-making in environments with changing action availability, where accessibility of the next action is…
A Unified Framework for Locality in Scalable MARL
Sourav Chakraborty, Amit Kiran Rege, Claire Monteleoni +1
Scalable methods for networked multi-agent reinforcement learning let each agent plan using only a small neighborhood of the agent graph. This works only when the system is value-l…