226 citations · 729 across the 62 of their papers we have counts for
7 papers · 2 filters
Algorithmically-Consistent Deep Learning Frameworks for Structural Topology Optimization
Jaydeep Rade, Aditya Balu, Ethan Herron +4
Topology optimization has emerged as a popular approach to refine a component's design and increase its performance. However, current state-of-the-art topology optimization framewo…
Decentralized Deep Learning using Momentum-Accelerated Consensus
Aditya Balu, Zhanhong Jiang, Sin Yong Tan +3
We consider the problem of decentralized deep learning where multiple agents collaborate to learn from a distributed dataset. While there exist several decentralized deep learning…
Query-based Targeted Action-Space Adversarial Policies on Deep Reinforcement Learning Agents
Xian Yeow Lee, Yasaman Esfandiari, Kai Liang Tan +1
Advances in computing resources have resulted in the increasing complexity of cyber-physical systems (CPS). As the complexity of CPS evolved, the focus has shifted from traditional…
Spatiotemporal Attention for Multivariate Time Series Prediction and Interpretation
Tryambak Gangopadhyay, Sin Yong Tan, Zhanhong Jiang +2
Multivariate time series modeling and prediction problems are abundant in many machine learning application domains. Accurate interpretation of such prediction outcomes from a mach…
Deep Generative Models that Solve PDEs: Distributed Computing for Training Large Data-Free Models
Sergio Botelho, Ameya Joshi, Biswajit Khara +4
Recent progress in scientific machine learning (SciML) has opened up the possibility of training novel neural network architectures that solve complex partial differential equation…
Robustifying Reinforcement Learning Agents via Action Space Adversarial Training
Kai Liang Tan, Yasaman Esfandiari, Xian Yeow Lee +2
Adoption of machine learning (ML)-enabled cyber-physical systems (CPS) are becoming prevalent in various sectors of modern society such as transportation, industrial, and power gri…
Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning
Johnathon Shook, Tryambak Gangopadhyay, Linjiang Wu +3
Accurate prediction of crop yield supported by scientific and domain-relevant insights, can help improve agricultural breeding, provide monitoring across diverse climatic condition…