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Towards Causal Representations of Climate Model Data
Climate models, such as Earth system models (ESMs), are crucial for simulating future climate change based on projected Shared Socioeconomic Pathways (SSP) greenhouse gas emissions scenarios.
Three-dimensional spike localization and improved motion correction for Neuropixels recordings
Neuropixels (NP) probes are dense linear multi-electrode arrays that have rapidly become essential tools for studying the electrophysiology of large neural populations.
Learning interpretable continuous-time models of latent stochastic dynamical systems
We develop an approach to learn an interpretable semi-parametric model of a latent continuous-time stochastic dynamical system, assuming noisy high-dimensional outputs sampled at uneven times.
Methods for Spoken Language Identification
In this paper, we explore several machine learning techniques for classifying spoken language.
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