fix: adjust figure size for scatter plot in generate_scatter_plot function

refactor: format code for readability in generate_scatter_plot function

feat: add depth slider and cache figures in BNN prior demo

feat: add SLURM array job for BNN prior depth sweep

feat: add BNN prior optimization demo page

fix: update save directory default and optimize inference for CPU device

refactor: inline inference into main(), add CLI args and save all artifacts to parameterized dir

fix: update bnn-priors git source from SSH to HTTPS in requirements and lock files

fix: update SLURM array range and reduce job time; add steps parameter to script

feat: work-in-progress on prior demo

fix: adjust training set size range and default value in UI

fix: use to_numpy() to fix Pylance type error on comparison

feat: use log scale x-axis for grokking plot with numbered ticks

feat: add SLURM array job for grokking sweep

fix: config adam correctly

fix: include pyarrow

revert: restore PEP 723 script for grokking training

feat: switch to CUDA 12.1 for PyTorch

feat: add CUDA 12.1 support for grokking script

cleanup: remove compute workspace and adjust layout

refactor: convert grokking script to PEP 723 format

feat: add grokking demo page with chat interface

feat: add grokking training script for modular arithmetic

feat: add DEMO_DATA_DIR env var for flexible data directory

feat: add Bayesian neural network uncertainty decomposition with Parquet caching

feat: improve covariance matrix visualization with color-coded crosshairs and scatter points

feat: reduce contour levels in GP joint distribution plot

feat: add Gaussian Process joint distribution visualization

feat: add deep net prior pathologies visualization

feat: add compute workspace for heavy model training

feat: add activation function selector for function space manifold plot

refactor: rename "ASI Demos" to "Demos" and finalize CLAUDE.md

fix: make sidebar expand button transparent but clickable

feat: upgrade Python version to 3.13 in Dockerfile and streamline application code copying

fix: use python -m streamlit to avoid shebang issue in multi-stage build

feat: update Dockerfile port to 7860 and include config.py

feat: add function space manifold visualization for Bayesian deep learning