6 papers
Optimization-based Online Conformal Prediction for Multi-step Forecasting
Ruipu Li, Daniel Menacho, Alexander RodrÃguez +1
Conformal prediction (CP) provides distribution-free coverage guarantees, making it well suited for uncertainty quantification in time series forecasting. However, existing methods…
Simulate, Reason, Decide: Scientific Reasoning with LLMs for Simulation-Driven Decision Making
Yuhan Yang, Ruipu Li, Alexander RodrÃguez
Scientific simulators are increasingly being integrated into LLM-driven systems for high-stakes simulation-driven decision-making. However, existing frameworks primarily use LLMs t…
Foundation Model in Biomedicine
Xiangrui Liu, Yuanyuan Zhang, Qianyu Shang +14
Foundation models, first introduced in 2021, refer to large-scale pretrained models (e.g., large language models (LLMs) and vision-language models (VLMs)) that learn from extensive…
Differentiable Electrochemistry: A paradigm for uncovering hidden physical phenomena in electrochemical systems
Haotian Chen, Chenyang Huang, Alexander RodrÃguez +2
Despite the long history of electrochemistry, there is a lack of quantitative algorithms that rigorously correlate experiment with theory. Electrochemical modeling has had advanced…
Counterfactual Probabilistic Diffusion with Expert Models
Wenhao Mu, Zhi Cao, Mehmed Uludag +1
Predicting counterfactual distributions in complex dynamical systems is essential for scientific modeling and decision-making in domains such as public health and medicine. However…
Neural Conformal Control for Time Series Forecasting
Ruipu Li, Alexander RodrÃguez
We introduce a neural network conformal prediction method for time series that enhances adaptivity in non-stationary environments. Our approach acts as a neural controller designed…