Understanding Place Identity with Generative AI

no code implementations • 7 Jun 2023 • Kee Moon Jang, Junda Chen, Yuhao Kang, Junghwan Kim, JinHyung Lee, Fábio Duarte

In this study, we aim to test the potential of generative AI as the source of textual and visual information in capturing the place identity of cities assessed by filtered descriptions and images.

Spike Sorting using the Neural Clustering Process

1 code implementation • NeurIPS Workshop Neuro_AI 2019 • Yueqi Wang, Ari Pakman, Catalin Mitelut, JinHyung Lee, Liam Paninski

We present a novel approach to spike sorting for high-density multielectrode probes using the Neural Clustering Process (NCP), a recently introduced neural architecture that performs scalable amortized approximate Bayesian inference for efficient probabilistic clustering.

Bayesian Inference Clustering +1

Neural Clustering Processes

5 code implementations • ICML 2020 • Ari Pakman, Yueqi Wang, Catalin Mitelut, JinHyung Lee, Liam Paninski

Probabilistic clustering models (or equivalently, mixture models) are basic building blocks in countless statistical models and involve latent random variables over discrete spaces.

Bayesian Inference Clustering +1