146 citations · 287 across the 12 of their papers we have counts for
15 papers
OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models
Anas Awadalla, Irena Gao, Josh Gardner +13
We introduce OpenFlamingo, a family of autoregressive vision-language models ranging from 3B to 9B parameters. OpenFlamingo is an ongoing effort to produce an open-source replicati…
VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use
Yonatan Bitton, Hritik Bansal, Jack Hessel +6
We introduce VisIT-Bench (Visual InsTruction Benchmark), a benchmark for evaluation of instruction-following vision-language models for real-world use. Our starting point is curati…
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation
Josh Gardner, Zoran Popović, Ludwig Schmidt
Researchers have proposed many methods for fair and robust machine learning, but comprehensive empirical evaluation of their subgroup robustness is lacking. In this work, we addres…
The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative Modeling
Yusong Wu, Josh Gardner, Ethan Manilow +3
Data is the lifeblood of modern machine learning systems, including for those in Music Information Retrieval (MIR). However, MIR has long been mired by small datasets and unreliabl…
Multi-instrument Music Synthesis with Spectrogram Diffusion
Curtis Hawthorne, Ian Simon, Adam Roberts +4
An ideal music synthesizer should be both interactive and expressive, generating high-fidelity audio in realtime for arbitrary combinations of instruments and notes. Recent neural…
MT3: Multi-Task Multitrack Music Transcription
Josh Gardner, Ian Simon, Ethan Manilow +2
Automatic Music Transcription (AMT), inferring musical notes from raw audio, is a challenging task at the core of music understanding. Unlike Automatic Speech Recognition (ASR), wh…
Driving with Data in the Motor City: Mining and Modeling Vehicle Fleet Maintenance Data
Josh Gardner, Jawad Mroueh, Natalia Jenuwine +4
The City of Detroit maintains an active fleet of over 2500 vehicles, spending an annual average of over $5 million on purchases and over $7.7 million on maintenance. Modeling pat…
Advances and Open Problems in Federated Learning
Peter Kairouz, H. Brendan McMahan, Brendan Avent +56
Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a cen…
Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments
Timothy NeCamp, Josh Gardner, Christopher Brooks
Randomized experiments ensure robust causal inference that are critical to effective learning analytics research and practice. However, traditional randomized experiments, like A/B…
Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining
Josh Gardner, Yuming Yang, Ryan Baker +1
The use of machine learning techniques has expanded in education research, driven by the rich data from digital learning environments and institutional data warehouses. However, re…
Dropout Model Evaluation in MOOCs
Josh Gardner, Christopher Brooks
The field of learning analytics needs to adopt a more rigorous approach for predictive model evaluation that matches the complex practice of model-building. In this work, we presen…
Evaluating Predictive Models of Student Success: Closing the Methodological Gap
Josh Gardner, Christopher Brooks
Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modeling research in learning analytics. We…
MORF: A Framework for Predictive Modeling and Replication At Scale With Privacy-Restricted MOOC Data
Josh Gardner, Christopher Brooks, Juan Miguel L. Andres +1
Big data repositories from online learning platforms such as Massive Open Online Courses (MOOCs) represent an unprecedented opportunity to advance research on education at scale an…
Student Success Prediction in MOOCs
Josh Gardner, Christopher Brooks
Predictive models of student success in Massive Open Online Courses (MOOCs) are a critical component of effective content personalization and adaptive interventions. In this articl…
Driving with Data: Modeling and Forecasting Vehicle Fleet Maintenance in Detroit
Josh Gardner, Danai Koutra, Jawad Mroueh +4
The City of Detroit maintains an active fleet of over 2500 vehicles, spending an annual average of over $5 million on new vehicle purchases and over $7.7 million on maintaining t…