124 citations · 213 across the 12 of their papers we have counts for
8 papers · 1 filter
Tracing the Unlabeled Storm: Cross-Variable Transfer in a Lagrangian Atmospheric JEPA Framework
K M Anirudh, S Sandeep, Hariprasad Kodamana
Deep atmospheric convection governs South Asian monsoon variability, yet attempting to learn its latent world model directly from zero-inflated, heavy-tailed precipitation yields s…
Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence
Mridul Gupta, Samyak Jain, Vansh Ramani +2
Graph Neural Networks (GNNs) are powerful tools for learning from graph-structured data, but their scalability is increasingly strained by the size of real-world graphs in domains…
Bonsai: Gradient-free Graph Condensation for Node Classification
Mridul Gupta, Samyak Jain, Vansh Ramani +2
Graph condensation has emerged as a promising avenue to enable scalable training of GNNs by compressing the training dataset while preserving essential graph characteristics. Our s…
Generative adversarial wavelet neural operator: Application to fault detection and isolation of multivariate time series data
Jyoti Rani, Tapas Tripura, Hariprasad Kodamana +1
Fault detection and isolation in complex systems are critical to ensure reliable and efficient operation. However, traditional fault detection methods often struggle with issues su…
Mirage: Model-Agnostic Graph Distillation for Graph Classification
Mridul Gupta, Sahil Manchanda, Hariprasad Kodamana +1
GNNs, like other deep learning models, are data and computation hungry. There is a pressing need to scale training of GNNs on large datasets to enable their usage on low-resource e…
FRIGATE: Frugal Spatio-temporal Forecasting on Road Networks
Mridul Gupta, Hariprasad Kodamana, Sayan Ranu
Modelling spatio-temporal processes on road networks is a task of growing importance. While significant progress has been made on developing spatio-temporal graph neural networks (…
TASAC: a twin-actor reinforcement learning framework with stochastic policy for batch process control
Tanuja Joshi, Hariprasad Kodamana, Harikumar Kandath +1
Due to their complex nonlinear dynamics and batch-to-batch variability, batch processes pose a challenge for process control. Due to the absence of accurate models and resulting pl…
Application of Machine Learning in understanding plant virus pathogenesis: Trends and perspectives on emergence, diagnosis, host-virus interplay and management
Dibyendu Ghosh, Srija Chakraborty, Hariprasad Kodamana +1
Inclusion of high throughput technologies in the field of biology has generated massive amounts of biological data in the recent years. Now, transforming these huge volumes of data…