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07/03/2023
SCITUNE: Aligning Large Language Models with Scientific Multimodal Instructions
Instruction finetuning is a popular paradigm to align large language mod...
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06/01/2023
A General Framework for Uncertainty Quantification via Neural SDE-RNN
Uncertainty quantification is a critical yet unsolved challenge for deep...
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05/31/2023
There is more to graphs than meets the eye: Learning universal features with self-supervision
We study the problem of learning universal features across multiple grap...
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06/16/2022
Challenges and Opportunities in Deep Reinforcement Learning with Graph Neural Networks: A Comprehensive review of Algorithms and Applications
Deep reinforcement learning (DRL) has empowered a variety of artificial ...
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05/30/2022
GraMeR: Graph Meta Reinforcement Learning for Multi-Objective Influence Maximization
Influence maximization (IM) is a combinatorial problem of identifying a ...
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05/20/2022
A General Framework for quantifying Aleatoric and Epistemic uncertainty in Graph Neural Networks
Graph Neural Networks (GNN) provide a powerful framework that elegantly ...
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12/26/2020
Bayesian Inductive Learner for Graph Resiliency under uncertainty
In the quest to improve efficiency, interdependence and complexity are b...
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12/26/2020
