226 citations · 729 across the 62 of their papers we have counts for
10 papers · 2 filters
MDPGT: Momentum-based Decentralized Policy Gradient Tracking
Zhanhong Jiang, Xian Yeow Lee, Sin Yong Tan +5
We propose a novel policy gradient method for multi-agent reinforcement learning, which leverages two different variance-reduction techniques and does not require large batches ove…
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs
Biswajit Khara, Aditya Balu, Ameya Joshi +4
We consider a mesh-based approach for training a neural network to produce field predictions of solutions to parametric partial differential equations (PDEs). This approach contras…
Cross-Modal Virtual Sensing for Combustion Instability Monitoring
Tryambak Gangopadhyay, Vikram Ramanan, Satyanarayanan R Chakravarthy +1
In many cyber-physical systems, imaging can be an important but expensive or 'difficult to deploy' sensing modality. One such example is detecting combustion instability using flam…
Differentiable Spline Approximations
Minsu Cho, Aditya Balu, Ameya Joshi +6
The paradigm of differentiable programming has significantly enhanced the scope of machine learning via the judicious use of gradient-based optimization. However, standard differen…
A Graph Policy Network Approach for Volt-Var Control in Power Distribution Systems
Xian Yeow Lee, Soumik Sarkar, Yubo Wang
Volt-var control (VVC) is the problem of operating power distribution systems within healthy regimes by controlling actuators in power systems. Existing works have mostly adopted t…
Distributed Multigrid Neural Solvers on Megavoxel Domains
Aditya Balu, Sergio Botelho, Biswajit Khara +6
We consider the distributed training of large-scale neural networks that serve as PDE solvers producing full field outputs. We specifically consider neural solvers for the generali…
Granger Causality Based Hierarchical Time Series Clustering for State Estimation
Sin Yong Tan, Homagni Saha, Margarite Jacoby +2
Clustering is an unsupervised learning technique that is useful when working with a large volume of unlabeled data. Complex dynamical systems in real life often entail data streami…
NURBS-Diff: A Differentiable Programming Module for NURBS
Anjana Deva Prasad, Aditya Balu, Harshil Shah +3
Boundary representations (B-reps) using Non-Uniform Rational B-splines (NURBS) are the de facto standard used in CAD, but their utility in deep learning-based approaches is not wel…
Cross-Gradient Aggregation for Decentralized Learning from Non-IID data
Yasaman Esfandiari, Sin Yong Tan, Zhanhong Jiang +4
Decentralized learning enables a group of collaborative agents to learn models using a distributed dataset without the need for a central parameter server. Recently, decentralized…
3D Convolutional Selective Autoencoder For Instability Detection in Combustion Systems
Tryambak Gangopadhyay, Vikram Ramanan, Adedotun Akintayo +4
While analytical solutions of critical (phase) transitions in physical systems are abundant for simple nonlinear systems, such analysis remains intractable for real-life dynamical…