{"payload":{"pageCount":2,"repositories":[{"type":"Public","name":"robust_decision_focused_rl_public","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-08-04T21:16:18.066Z"}},{"type":"Public","name":"rethinking_discount_reg_public","owner":"dtak","isFork":false,"description":"Simulations for the paper: \"Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning\"","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-18T14:25:11.532Z"}},{"type":"Public","name":"dtak.github.io","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"JavaScript","color":"#f1e05a"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-09-11T18:20:15.723Z"}},{"type":"Public","name":"signature-activation","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-07-26T18:50:28.817Z"}},{"type":"Public","name":"kernel_mismatch_workshop","owner":"dtak","isFork":false,"description":"Code for Implications of Gaussian process kernel mismatch for out-of-distribution data (ICML 2023 workshops)","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-06-30T04:19:36.022Z"}},{"type":"Public","name":"anchor-box","owner":"dtak","isFork":false,"description":"This repository contains the code for out work, Guarantee Regions for Local Explanations","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-01-31T18:14:20.422Z"}},{"type":"Public","name":"adversarial-robustness-public","owner":"dtak","isFork":false,"description":"Code for AAAI 2018 accepted paper: \"Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients\"","allTopics":["robustness","interpretability"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":1,"issueCount":3,"starsCount":53,"forksCount":14,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-12-04T17:11:13.510Z"}},{"type":"Public","name":"addressing-leakage","owner":"dtak","isFork":false,"description":"Code for the paper 'Addressing leakage in Concept Bottleneck Models'","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":6,"forksCount":1,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-10-11T17:47:56.793Z"}},{"type":"Public","name":"optimal-summaries-public","owner":"dtak","isFork":false,"description":"Code repository for the MLHC 2022 paper \"Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models\"","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":3,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-07-27T23:44:59.200Z"}},{"type":"Public","name":"Decision-Region-for-ICU-Hypotension","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":5,"forksCount":3,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-07-14T01:54:57.258Z"}},{"type":"Public","name":"ocbnn-public","owner":"dtak","isFork":false,"description":"General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.","allTopics":["bayesian-neural-networks","bayesian-deep-learning","paper","bnns","oc-bnn"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":2,"issueCount":0,"starsCount":38,"forksCount":5,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-06-21T22:38:14.290Z"}},{"type":"Public","name":"kernel-evolutions-public","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-05-23T19:32:06.369Z"}},{"type":"Public","name":"wide-bnns-public","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":3,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-02-23T16:46:28.879Z"}},{"type":"Public","name":"power-constrained-bandits-public","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":3,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-07-28T07:32:45.906Z"}},{"type":"Public","name":"hierarchical-disentanglement","owner":"dtak","isFork":false,"description":"Code for Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement","allTopics":["hierarchy","representation-learning","disentanglement"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":5,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-06-12T15:26:38.656Z"}},{"type":"Public","name":"osiris","owner":"dtak","isFork":false,"description":"Omitting-States-Irrelevant-to-Return Importance Sampling estimator for off-policy evaluation","allTopics":["reinforcement-learning","importance-sampling","off-policy-evaluation"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-06-11T07:03:07.072Z"}},{"type":"Public","name":"POPCORN-POMDP","owner":"dtak","isFork":false,"description":"Implementation of \"POPCORN: Partially Observed Prediction Constrained Reinforcement Learning\" (Futoma, Hughes, Doshi-Velez, AISTATS 2020)","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":2,"starsCount":11,"forksCount":2,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-05-19T00:42:17.610Z"}},{"type":"Public","name":"interactive-reconstruction","owner":"dtak","isFork":false,"description":"Code for Evaluating the Interpretability of Generative Models by Interactive Reconstruction","allTopics":["representation-learning","interpretability"],"primaryLanguage":{"name":"HTML","color":"#e34c26"},"pullRequestCount":0,"issueCount":0,"starsCount":9,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-02-03T02:50:07.378Z"}},{"type":"Public","name":"rrr","owner":"dtak","isFork":false,"description":"Code/figures in Right for the Right Reasons","allTopics":["interpretability"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":3,"starsCount":54,"forksCount":11,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-12-29T16:56:07.354Z"}},{"type":"Public","name":"tensorpack","owner":"dtak","isFork":true,"description":"A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":1811,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-12-28T16:10:52.953Z"}},{"type":"Public","name":"mbrl-smdp-ode","owner":"dtak","isFork":false,"description":"PyTorch implementation of \"Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs\", NeurIPS 2020","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":2,"starsCount":36,"forksCount":5,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-10-25T06:10:42.026Z"}},{"type":"Public","name":"porbnet","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-08-05T03:47:58.387Z"}},{"type":"Public","name":"interpretable_ope_public","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":6,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-06-28T16:35:41.450Z"}},{"type":"Public","name":"prediction-constrained-topic-models","owner":"dtak","isFork":false,"description":"Public repo containing code to train, visualize, and evaluate semi-supervised topic models and baselines for regression/classification on labeled bag-of-words dataset, as described in Hughes et al. AISTATS 2018","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":1,"issueCount":0,"starsCount":12,"forksCount":5,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-04-15T19:36:13.889Z"}},{"type":"Public","name":"umls_tagger","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2019-12-05T18:31:02.388Z"}},{"type":"Public","name":"pgmult","owner":"dtak","isFork":true,"description":"Dependent multinomials made easy: stick-breaking with the PĆ³lya-gamma augmentation","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":2,"issueCount":0,"starsCount":0,"forksCount":22,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2019-12-05T17:49:52.969Z"}},{"type":"Public","name":"i-airl","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2019-12-04T23:49:13.246Z"}},{"type":"Public","name":"local-independence-public","owner":"dtak","isFork":false,"description":"Code/figures in Learning Qualitatively Diverse and Interpretable Rules for Classification","allTopics":["interpretability","multiple-solutions"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":5,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2019-11-27T14:24:11.371Z"}},{"type":"Public","name":"lit","owner":"dtak","isFork":false,"description":"Code for AAAI 2020 paper \"Ensembles of Locally Independent Prediction Models\"","allTopics":["multiple-solutions"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":8,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2019-11-27T14:23:08.304Z"}},{"type":"Public","name":"dynamic-mixing","owner":"dtak","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"OpenEdge ABL","color":"#5ce600"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2019-11-21T18:06:33.233Z"}}],"repositoryCount":43,"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":"dtak repositories"}