109 citations · 190 across the 5 of their papers we have counts for
5 papers
Fine-tuning Protein Language Models with Deep Mutational Scanning improves Variant Effect Prediction
Aleix Lafita, Ferran Gonzalez, Mahmoud Hossam +5
Protein Language Models (PLMs) have emerged as performant and scalable tools for predicting the functional impact and clinical significance of protein-coding variants, but they sti…
Delving Deeper into MOOC Student Dropout Prediction
Jacob Whitehill, Kiran Mohan, Daniel Seaton +2
In order to obtain reliable accuracy estimates for automatic MOOC dropout predictors, it is important to train and test them in a manner consistent with how they will be used in pr…
Exploring University Students' Engagement with Online Video Lectures in a Blended Introductory Mechanics Course
Shih-Yin Lin, John M. Aiken, Daniel T. Seaton +4
The advent of MOOCs has stimulated interest in using online videos to deliver content in university courses. We examined student engagement with 78 online videos that we created an…
Participation And performance In 8.02x Electricity And Magnetism: The First Physics MOOC From MITx
Saif Rayyan, Daniel T. Seaton, John Belcher +2
Massive Open Online Courses are an exciting new avenue for instruction and research, yet they are full of unknowns. In the Spring of 2013, MITx released its first introductory phys…
Microcanonical entropy inflection points: Key to systematic understanding of transitions in finite systems
Stefan Schnabel, Daniel T. Seaton, David P. Landau +1
We introduce a systematic classification method for the analogs of phase transitions in finite systems. This completely general analysis, which is applicable to any physical system…