5 citations · 25 across the 15 of their papers we have counts for
4 papers · 2 filters
Automatically Learning Hybrid Digital Twins of Dynamical Systems
Samuel Holt, Tennison Liu, Mihaela van der Schaar
Digital Twins (DTs) are computational models that simulate the states and temporal dynamics of real-world systems, playing a crucial role in prediction, understanding, and decision…
Discovering Preference Optimization Algorithms with and for Large Language Models
Chris Lu, Samuel Holt, Claudio Fanconi +4
Offline preference optimization is a key method for enhancing and controlling the quality of Large Language Model (LLM) outputs. Typically, preference optimization is approached as…
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference
Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets +2
Inferring unbiased treatment effects has received widespread attention in the machine learning community. In recent years, our community has proposed numerous solutions in standard…
Dense Reward for Free in Reinforcement Learning from Human Feedback
Alex J. Chan, Hao Sun, Samuel Holt +1
Reinforcement Learning from Human Feedback (RLHF) has been credited as the key advance that has allowed Large Language Models (LLMs) to effectively follow instructions and produce…