Computer Science - Machine Learning

Beyond Forecasting: Compositional Time Series Reasoning for End-to-End Task Execution
In recent decades, there has been substantial advances in time series models and benchmarks across various individual tasks, such as …
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TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model
With recent advances in building foundation models for texts and video data, there is a surge of interest in foundation models for time …
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An Examination on the Effectiveness of Divide-and-Conquer Prompting in Large Language Models
Foundation models, such as Large language Models (LLMs), have attracted significant amount of interest due to their large number of …
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TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
The past decade has witnessed significant advances in time series modeling with deep learning. While achieving state-of-the-art …
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Sparse Interaction Additive Networks via Feature Interaction Detection and Sparse Selection
There is currently a large gap in performance between the statistically rigorous methods like linear regression or additive splines and …
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Estimating Treatment Effects in Continuous Time with Hidden Confounders
Estimating treatment effects plays a crucial role in causal inference, having many real-world applications like policy analysis and …
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DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift
In electronic trading markets, limit order books (LOBs) provide information about pending buy/sell orders at various price levels for a …
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Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media
Recent years have witnessed the rise of misinformation campaigns that spread specific narratives on social media to manipulate public …
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When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning
Physics-informed machine learning (PIML), referring to the combination of prior knowledge of physics, which is the high level …
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VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media
Recent years have witnessed an increasing use of coordinated accounts on social media, operated by misinformation campaigns to …
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