Estimating Noise Correlations Across Continuous Conditions With Wishart Processes
Authors: Amin Nejatbakhsh, Isabel Garon, Alex Williams
NeurIPS 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate that these models perform favorably on experimental data from the mouse visual cortex and monkey motor cortex relative to standard covariance estimators. |
| Researcher Affiliation | Collaboration | Amin Nejatbakhsh Isabel Garon Alex H Williams Center for Neural Science, New York University, New York, NY Center for Computational Neuroscience, Flatiron Institute, New York, NY {anejatbakhsh,igaron,awilliams}@flatironinstitute.org |
| Pseudocode | No | The paper does not contain a section or figure explicitly labeled 'Pseudocode' or 'Algorithm'. |
| Open Source Code | Yes | All codes are implemented in numpyro [50] and available at https://github.com/neurostatslab/wishart-process. |
| Open Datasets | Yes | To investigate, we analyzed simultaneously recorded responses in mouse primary visual cortex to drifting visual gratings in the Allen Brain Observatory (Visual Coding: Neuropixels dataset).4 https://portal.brain-map.org/explore/circuits/visual-coding-neuropixels |
| Dataset Splits | Yes | Models were fitted on 60% of the available trials, radial and angular smoothness parameters for both GP and WP kernels were selected on a validation set of 25% of the data, and log-likelihood scores were generated using the remaining 15% of trials. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU/CPU models, memory, or cloud instances) used for running the experiments. |
| Software Dependencies | No | The paper states 'All codes are implemented in numpyro [50]' but does not provide a specific version number for numpyro or any other software dependencies. |
| Experiment Setup | Yes | All other hyperparameters are kept constant (P = 2, γ = 0.001, β = 1, and λµ = 1). ... the optimal performance of the Wishart model is achieved for λΣ 1.5 and P = 0. |