203 citations · 224 across the 17 of their papers we have counts for
6 papers · 1 filter
Regression with Large Language Models for Materials and Molecular Property Prediction
Ryan Jacobs, Maciej P. Polak, Lane E. Schultz +3
We demonstrate the ability of large language models (LLMs) to perform material and molecular property regression tasks, a significant deviation from the conventional LLM use case.…
MolBind: Multimodal Alignment of Language, Molecules, and Proteins
Teng Xiao, Chao Cui, Huaisheng Zhu +1
Recent advancements in biology and chemistry have leveraged multi-modal learning, integrating molecules and their natural language descriptions to enhance drug discovery. However,…
Causal Effect Estimation Using Random Hyperplane Tessellations
Abhishek Dalvi, Neil Ashtekar, Vasant Honavar
Matching is one of the simplest approaches for estimating causal effects from observational data. Matching techniques compare the observed outcomes across pairs of individuals with…
3M-Diffusion: Latent Multi-Modal Diffusion for Language-Guided Molecular Structure Generation
Huaisheng Zhu, Teng Xiao, Vasant G Honavar
Generating molecular structures with desired properties is a critical task with broad applications in drug discovery and materials design. We propose 3M-Diffusion, a novel multi-mo…
Hyperdimensional Representation Learning for Node Classification and Link Prediction
Abhishek Dalvi, Vasant Honavar
We introduce Hyperdimensional Graph Learner (HDGL), a novel method for node classification and link prediction in graphs. HDGL maps node features into a very high-dimensional space…
EsaCL: Efficient Continual Learning of Sparse Models
Weijieying Ren, Vasant G Honavar
A key challenge in the continual learning setting is to efficiently learn a sequence of tasks without forgetting how to perform previously learned tasks. Many existing approaches t…