5 citations · 5 across the 4 of their papers we have counts for
5 papers
RangeFinder: Predicting Ligand Property Ranges from Protein Pockets
Alan Nadelsticher Ruvalcaba, Chris Alvin, Supratik Mukhopadhyay +1
Identifying ligands for a protein target requires searching a vast chemical space for a comparatively small set of compatible molecules. Existing machine learning approaches primar…
Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification
Varad Shinde, Nikhil Kumar Shrey, Magesh Rajasekaran +5
Deep learning models in computer vision face significant challenges when trained on long-tailed datasets, where a few majority classes dominate while many minority classes are seve…
Benchmarking Artificial Intelligence Models for Daily Coastal Hypoxia Forecasting
Magesh Rajasekaran, Md Saiful Sajol, Chris Alvin +3
Coastal hypoxia, especially in the northern part of Gulf of Mexico, presents a persistent ecological and economic concern. Seasonal models offer coarse forecasts that miss the fine…
COMBOOD: A Semiparametric Approach for Detecting Out-of-distribution Data for Image Classification
Magesh Rajasekaran, Md Saiful Islam Sajol, Frej Berglind +2
Identifying out-of-distribution (OOD) data at inference time is crucial for many machine learning applications, especially for automation. We present a novel unsupervised semi-para…
A Multimodal Human Protein Embeddings Database: DeepDrug Protein Embeddings Bank (DPEB)
Md Saiful Islam Sajol, Magesh Rajasekaran, Hayden Gemeinhardt +3
Computationally predicting protein-protein interactions (PPIs) is challenging due to the lack of integrated, multimodal protein representations. DPEB is a curated collection of 22,…