{"payload":{"pageCount":3,"repositories":[{"type":"Public","name":"self-driving-lab-demo","owner":"sparks-baird","isFork":false,"description":"Software and instructions for setting up and running a self-driving lab (autonomous experimentation) demo using dimmable RGB LEDs, an 8-channel spectrophotometer, a microcontroller, and an adaptive design algorithm, as well as extensions to liquid- and solid-based color matching demos.","allTopics":["raspberry-pi","neopixel","machine-learning","automation","micropython","optics","materials-science","materials-informatics","circuitpython","bayesian-optimization","closed-loop","adaptive-design","rpi-pico","as7341","pico-wireless","self-driving-lab","pico-w","smart-lab","internet-of-laboratory-things","python"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":33,"starsCount":63,"forksCount":7,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-13T16:30:25.905Z"}},{"type":"Public","name":"matbench-genmetrics","owner":"sparks-baird","isFork":false,"description":"Generative materials benchmarking metrics, inspired by guacamol and CDVAE.","allTopics":["materials-informatics","python"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":17,"starsCount":30,"forksCount":2,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-01T03:47:34.828Z"}},{"type":"Public","name":"matsci-opt-benchmarks","owner":"sparks-baird","isFork":false,"description":"A collection of benchmarking problems and datasets for testing the performance of advanced optimization algorithms in the field of materials science and chemistry.","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":6,"starsCount":9,"forksCount":1,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-16T20:39:54.141Z"}},{"type":"Public","name":"mat_discover","owner":"sparks-baird","isFork":false,"description":"A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.","allTopics":["pytorch","materials-science","materials-informatics","numba","bayesian-optimization","wasserstein","earth-movers-distance","materials-screening","materials-discoveries","adaptive-design","wasserstein-metric","earth-mover-distance","wasserstein-distance","crabnet","predict-materials-properties","materials-discovery","materials-project","matdiscover","python","machine-learning"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":5,"issueCount":24,"starsCount":35,"forksCount":9,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-11-06T21:31:48.477Z"}},{"type":"Public","name":"xtal2png","owner":"sparks-baird","isFork":false,"description":"Encode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning models such as Palette.","allTopics":["image-processing","crystallography","materials-science","materials-informatics","python","machine-learning"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":3,"issueCount":26,"starsCount":34,"forksCount":3,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-10-04T00:53:43.486Z"}},{"type":"Public","name":".github","owner":"sparks-baird","isFork":false,"description":"","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-08-07T14:39:32.738Z"}},{"type":"Public","name":"CBFV","owner":"sparks-baird","isFork":true,"description":"Tool to quickly create a composition-based feature vector","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":4,"forksCount":6,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-06-27T00:07:42.618Z"}},{"type":"Public","name":"dist-matrix","owner":"sparks-baird","isFork":false,"description":"Fast Numba-enabled CPU and GPU computations of Earth Mover's (scipy.stats.wasserstein_distance) and Euclidean distances.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":2,"issueCount":0,"starsCount":14,"forksCount":3,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-06-23T01:00:23.068Z"}},{"type":"Public","name":"gridrdf","owner":"sparks-baird","isFork":true,"description":"Code for calculating grouped representation of interatomic distances (GRID) from crystal structures, and applying this in machine learning models.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":3,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-06-22T22:56:42.392Z"}},{"type":"Public","name":"chem_wasserstein","owner":"sparks-baird","isFork":true,"description":"A high performance mapping class to construct ElM2D plots from large datasets of inorganic compositions.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":3,"starsCount":4,"forksCount":3,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-06-19T09:53:47.016Z"}},{"type":"Public","name":"CrabNet","owner":"sparks-baird","isFork":true,"description":"Predict materials properties using only the composition information!","allTopics":["python","machine-learning","pytorch","materials-science","materials-informatics","attention-mechanism","attention-is-all-you-need","materials-screening","self-attention","materials-genome","predict-materials-properties","materials-discovery"],"primaryLanguage":{"name":"HTML","color":"#e34c26"},"pullRequestCount":6,"issueCount":15,"starsCount":12,"forksCount":24,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-06-19T09:35:52.337Z"}},{"type":"Public archive","name":"mp-time-split","owner":"sparks-baird","isFork":false,"description":"Use time-splits for Materials Project entries for generative modeling benchmarking.","allTopics":["materials-science","materials-informatics","generative","time-series-forecasting","materials-project"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":8,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-06-17T21:30:44.968Z"}},{"type":"Public","name":"uh2pt-furnace","owner":"sparks-baird","isFork":false,"description":"Ultra-high purity, ultra-high temperature furnace capable of up to 3000 °C","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-04-27T06:18:27.267Z"}},{"type":"Public","name":"olympus","owner":"sparks-baird","isFork":true,"description":"Olympus: a benchmarking framework for noisy optimization and experiment planning","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":23,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-04-23T20:30:42.807Z"}},{"type":"Public","name":"bayes-opt-particle-packing","owner":"sparks-baird","isFork":false,"description":"Compactness Matters: Improving Bayesian Optimization Efficiency of Materials Formulations through Invariant Search Spaces","allTopics":["materials-informatics","adaptive-experimentation-platform","python","optimization"],"primaryLanguage":{"name":"HTML","color":"#e34c26"},"pullRequestCount":0,"issueCount":1,"starsCount":6,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-03-02T19:06:06.872Z"}},{"type":"Public","name":"Ax","owner":"sparks-baird","isFork":true,"description":"Adaptive Experimentation Platform","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":295,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-02-18T21:22:08.597Z"}},{"type":"Public","name":"auto-paper","owner":"sparks-baird","isFork":false,"description":"The aim of auto-paper is to give you tips, tricks, and tools to accelerate your publication rate and improve publication quality.","allTopics":["python","latex","version-control","matlab","typesetting","mathematica","latex-template","tables","latex-package","literature-review","figures","literature-search","reference-management"],"primaryLanguage":{"name":"Mathematica","color":"#dd1100"},"pullRequestCount":0,"issueCount":2,"starsCount":59,"forksCount":7,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-02-04T08:06:28.644Z"}},{"type":"Public","name":"composition-based-stability-regression","owner":"sparks-baird","isFork":false,"description":"Testing out the performance of CrabNet on predicting stability using only compositional features.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":3,"starsCount":2,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-01-08T06:21:24.236Z"}},{"type":"Public","name":"tox-debug","owner":"sparks-baird","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":1,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-12-11T05:11:13.767Z"}},{"type":"Public","name":"packing-generation","owner":"sparks-baird","isFork":true,"description":"Hard-sphere packing generation with the Lubachevsky–Stillinger, Jodrey–Tory, and force-biased algorithms and packing post-processing.","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":42,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-11-21T19:02:59.981Z"}},{"type":"Public","name":"xtal2png-imagen-pytorch-notebooks","owner":"sparks-baird","isFork":false,"description":"Saving notebooks as I run them, even if I might not end up using them for a manuscript and especially to preserve history when I overwrite them.","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-10-06T02:19:24.095Z"}},{"type":"Public","name":"staged-recipes","owner":"sparks-baird","isFork":true,"description":"A place to submit conda recipes before they become fully fledged conda-forge feedstocks","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":4699,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-08-24T00:57:59.347Z"}},{"type":"Public","name":"optimization-benchmark","owner":"sparks-baird","isFork":false,"description":"A high-dimensional property predictor framed as a pseudo-materials discovery benchmark with fake compositional (linear) and \"no-more-than-X-components\" (non-linear) constraints.","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":5,"starsCount":4,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-08-03T04:44:17.060Z"}},{"type":"Public","name":"matbench","owner":"sparks-baird","isFork":true,"description":"Matbench: Benchmarks for materials science property prediction","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":42,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-07-27T17:42:21.921Z"}},{"type":"Public","name":"MLSummerSchoolVienna2022","owner":"sparks-baird","isFork":true,"description":"ESI-DCAFM-TACO-VDSP Summer School on \"Machine Learning for Materials Hard and Soft\"","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":22,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-07-22T00:16:17.550Z"}},{"type":"Public","name":"crabnet-hyperparameter","owner":"sparks-baird","isFork":false,"description":"Using Bayesian optimization via Ax platform + SAASBO model to simultaneously optimize 23 hyperparameters in 100 iterations (set a new Matbench benchmark).","allTopics":["benchmark","materials-informatics","bayesian-optimization","adaptive-design","transformer-network","adaptive-experimentation-platform","materials-discovery","machine-learning"],"primaryLanguage":{"name":"HTML","color":"#e34c26"},"pullRequestCount":0,"issueCount":1,"starsCount":3,"forksCount":1,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-07-08T20:05:32.989Z"}},{"type":"Public","name":"techblick-robotics-ai-notes","owner":"sparks-baird","isFork":false,"description":"","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-06-16T22:50:03.212Z"}},{"type":"Public","name":"cdvae","owner":"sparks-baird","isFork":true,"description":"An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":83,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-06-12T05:39:39.898Z"}},{"type":"Public","name":"Palette-Image-to-Image-Diffusion-Models","owner":"sparks-baird","isFork":true,"description":"Unofficial implementation of Palette: Image-to-Image Diffusion Models by Pytorch","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":188,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-06-10T04:45:57.022Z"}},{"type":"Public","name":"numba","owner":"sparks-baird","isFork":true,"description":"NumPy aware dynamic Python compiler using LLVM","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":1,"issueCount":0,"starsCount":0,"forksCount":1109,"license":"BSD 2-Clause \"Simplified\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-06-07T20:24:43.179Z"}}],"repositoryCount":64,"userInfo":null,"searchable":true,"definitions":[],"typeFilters":[{"id":"all","text":"All"},{"id":"public","text":"Public"},{"id":"source","text":"Sources"},{"id":"fork","text":"Forks"},{"id":"archived","text":"Archived"},{"id":"template","text":"Templates"}],"compactMode":false},"title":"Repositories"}