9 papers
CellBRIDGE: Learning Cellular Trajectories via Interaction-Aware Alignment
Silas Ruhrberg Estévez, Nicolas Huynh, Tennison Liu +4
Inferring dynamics from population snapshots is a fundamental challenge in machine learning and biology. In scRNA-sequencing (scRNA-seq), destructive measurements preclude direct t…
WavesFM: Hierarchical Representation Learning for Longitudinal Wearable Sensor Waveforms
Peng Cao, Zhijian Yang, Tennison Liu +17
Wearable sensors enable the continuous acquisition of high-resolution physiological waveforms, such as photoplethysmography and accelerometry, under free-living conditions. However…
Hypothesis Hunting with Evolving Networks of Autonomous Scientific Agents
Tennison Liu, Silas Ruhrberg Estévez, David L. Bentley +1
Large-scale scientific datasets -- spanning health biobanks, cell atlases, Earth reanalyses, and more -- create opportunities for exploratory discovery unconstrained by specific re…
Truly Self-Improving Agents Require Intrinsic Metacognitive Learning
Tennison Liu, Mihaela van der Schaar
Self-improving agents aim to continuously acquire new capabilities with minimal supervision. However, current approaches face two key limitations: their self-improvement processes…
Autoformulation of Mathematical Optimization Models Using LLMs
Nicolás Astorga, Tennison Liu, Yuanzhang Xiao +1
Mathematical optimization is fundamental to decision-making across diverse domains, from operations research to healthcare. Yet, translating real-world problems into optimization m…
Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets
Simpson Zhang, Tennison Liu, Mihaela van der Schaar
Current labor markets are strongly affected by the economic forces of adverse selection, moral hazard, and reputation, each of which arises due to …