Josh Gardner
Orcid: 0000-0002-4998-5918Affiliations:
- University of Washington, USA
- Google Research, Brain Team, USA
- University of Michigan, Ann Arbor, MI, USA (former)
According to our database1,
Josh Gardner
authored at least 37 papers
between 2017 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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Bibliography
2024
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use.
CoRR, 2023
OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023
2022
The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative Modeling.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the 23rd International Society for Music Information Retrieval Conference, 2022
Proceedings of the 23rd International Society for Music Information Retrieval Conference, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
Towards Culturally Relevant Personalization at Scale: Experiments with Data Science Learners.
Int. J. Artif. Intell. Educ., 2021
2020
Driving with Data in the Motor City: Mining and Modeling Vehicle Fleet Maintenance Data.
CoRR, 2020
Driving with Data in the Motor City: Understanding and Predicting Fleet Maintenance Patterns.
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020
2019
Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments.
Proceedings of the 9th International Conference on Learning Analytics & Knowledge, 2019
Proceedings of the 9th International Conference on Learning Analytics & Knowledge, 2019
Modeling and Experimental Design for MOOC Dropout Prediction: A Replication Perspective.
Proceedings of the 12th International Conference on Educational Data Mining, 2019
2018
Learn From Your (Markov) Neighbor: Coenrollment, Assortativity, and Grade Prediction in Undergraduate Courses.
J. Learn. Anal., November, 2018
J. Learn. Anal., August, 2018
Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining.
CoRR, 2018
Proceedings of the Fifth Annual ACM Conference on Learning at Scale, 2018
Proceedings of the 8th International Conference on Learning Analytics and Knowledge, 2018
Proceedings of the Rethinking learning in the digital age: Making the Learning Sciences count, 2018
MORF: A Framework for Predictive Modeling and Replication At Scale With Privacy-Restricted MOOC Data.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
CoRR, 2017
Proceedings of the Fourth ACM Conference on Learning @ Scale, 2017
Proceedings of the Seventh International Learning Analytics & Knowledge Conference, 2017
Proceedings of the Joint Proceedings of the Workshop on Methodology in Learning Analytics (MLA) and the Workshop on Building the Learning Analytics Curriculum (BLAC) co-located with 7th International Learning Analytics and Knowledge Conference (LAK 2017), 2017
Proceedings of the 10th International Conference on Educational Data Mining, 2017