activity
20192026
most citedCounterfactual Phenotyping with Censored Time-to-Events

27 citations · 87 across the 24 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.AI2024

TimeSeriesExam: A time series understanding exam

Yifu Cai, Arjun Choudhry, Mononito Goswami +1

Large Language Models (LLMs) have recently demonstrated a remarkable ability to model time series data. These capabilities can be partly explained if LLMs understand basic time ser…

cs.LG2024

Towards Long-Context Time Series Foundation Models

Nina Żukowska, Mononito Goswami, Michał Wiliński +2

Time series foundation models have shown impressive performance on a variety of tasks, across a wide range of domains, even in zero-shot settings. However, most of these models are…

cs.LG2024

Exploring Representations and Interventions in Time Series Foundation Models

Michał Wiliński, Mononito Goswami, Willa Potosnak +2

Time series foundation models (TSFMs) promise to be powerful tools for a wide range of applications. However, their internal representations and learned concepts are still not well…

cs.LG2024

Implicit Reasoning in Deep Time Series Forecasting

Willa Potosnak, Cristian Challu, Mononito Goswami +3

Recently, time series foundation models have shown promising zero-shot forecasting performance on time series from a wide range of domains. However, it remains unclear whether thei…

cs.LG2024★ 27 cited

MOMENT: A Family of Open Time-series Foundation Models

Mononito Goswami, Konrad Szafer, Arjun Choudhry +3

We introduce MOMENT, a family of open-source foundation models for general-purpose time series analysis. Pre-training large models on time series data is challenging due to (1) the…