4 papers
Brain-Inspired Stochastic Joint Embedding Representation Learning
Makoto Yamada, Kian Ming A. Chai, Ayoub Rhim +3
Representation learning is one of the key research topics in machine learning, and the framework of self-supervised learning (SSL) has revolutionized computer vision. However, thes…
Rethinking Molecular Text Representations for LLMs: An Empirical Study
Arun Raja, Garrett M. Morris, Kian Ming A. Chai
Large language models (LLMs) are increasingly used for molecular tasks, but it remains unclear which molecular representation to use. We present a systematic benchmark evaluating L…
Variational Learning of Fractional Posteriors
Kian Ming A. Chai, Edwin V. Bonilla
We introduce a novel one-parameter variational objective that lower bounds the data evidence and enables the estimation of approximate fractional posteriors. We extend this framewo…
Thompson Sampling in Function Spaces via Neural Operators
Rafael Oliveira, Xuesong Wang, Kian Ming A. Chai +1
We propose an extension of Thompson sampling to optimization problems over function spaces where the objective is a known functional of an unknown operator's output. We assume that…