6 papers
Model Agnostic Graph Prompt Learning for Crystal Property Prediction
Shrimon Mukherjee, Kishalay Das, Partha Basuchowdhuri +2
Graph Neural Networks have emerged as a powerful tool for the fast and accurate prediction of various crystal properties. These models often encode domain-specific knowledge into t…
Generating crossmodal gene expression from cancer histopathology improves multimodal AI predictions
Samiran Dey, Christopher R. S. Banerji, Partha Basuchowdhuri +3
Emerging research has highlighted that artificial intelligence-based multimodal fusion of digital pathology and transcriptomic features can improve cancer diagnosis (grading/subtyp…
Unified Graph Networks (UGN): A Deep Neural Framework for Solving Graph Problems
Rudrajit Dawn, Madhusudan Ghosh, Partha Basuchowdhuri +1
Deep neural networks have enabled researchers to create powerful generalized frameworks, such as transformers, that can be used to solve well-studied problems in various applicatio…
AlpaPICO: Extraction of PICO Frames from Clinical Trial Documents Using LLMs
Madhusudan Ghosh, Shrimon Mukherjee, Asmit Ganguly +3
In recent years, there has been a surge in the publication of clinical trial reports, making it challenging to conduct systematic reviews. Automatically extracting Population, Inte…
CrysAtom: Distributed Representation of Atoms for Crystal Property Prediction
Shrimon Mukherjee, Madhusudan Ghosh, Partha Basuchowdhuri
Application of artificial intelligence (AI) has been ubiquitous in the growth of research in the areas of basic sciences. Frequent use of machine learning (ML) and deep learning (D…
An Algorithm for the Decomposition of Complete Graph into Minimum Number of Edge-disjoint Trees
Antika Sinha, Sanjoy Kumar Saha, Partha Basuchowdhuri
In this work, we study methodical decomposition of an undirected, unweighted complete graph ( of order , size ) into minimum number of edge-disjoint trees. We find that…