3 citations · 4 across the 4 of their papers we have counts for
5 papers
Morpheus-2.0: Multiscale Probabilistic Forecasting with Dual-Axis Attention
Aakriti, Manoj Cherukumalli, Prathamesh Patil +5
A universal forecaster is trained once and applied everywhere, so it must serve tasks whose schemas, forecast horizons, and temporal resolutions all differ. The number of targets a…
Dynamic Linear Coregionalization for Realistic Synthetic Multivariate Time Series
Annita Vapsi, Penghang Liu, Saheed Obitayo +8
Synthetic data is essential for training foundation models for time series (FMTS), but most generators assume static correlations, and are typically missing realistic inter-channel…
Privacy-Aware Time Series Synthesis via Public Knowledge Distillation
Penghang Liu, Haibei Zhu, Eleonora Kreacic +1
Sharing sensitive time series data in domains such as finance, healthcare, and energy consumption, such as patient records or investment accounts, is often restricted due to privac…
TS-Agent: Understanding and Reasoning Over Raw Time Series via Iterative Insight Gathering
Penghang Liu, Elizabeth Fons, Annita Vapsi +5
Large language models (LLMs) exhibit strong symbolic and compositional reasoning, yet they struggle with time series question answering as the data is typically transformed into an…
LLM-driven Imitation of Subrational Behavior : Illusion or Reality?
Andrea Coletta, Kshama Dwarakanath, Penghang Liu +2
Modeling subrational agents, such as humans or economic households, is inherently challenging due to the difficulty in calibrating reinforcement learning models or collecting data…