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Madhav Marathe

15 accepted papers

2026

AG-STELLA: Spatio-Temporal Learning for Water-related Agricultural Land Use Activity Mapping with AlphaEarth

Nibir Chandra Mandal, Oishee Bintey Hoque, Kyle Luong, Samarth Swarup, Kirti Rajagopalan, Mandy Wilson +2
IJCAI 2026

Accurate mapping of agricultural land use activity, particularly long-term transition from cropland to pasture and short-term transition between cropland to fallow land, is essential for sustainable water management, drought response, and food-system resilience which directly supports United Nations

Cited by 0Scholar ↗
2026

Information Theoretic Optimal Surveillance for Epidemic Prevalence in Networks

Ritwick Mishra, Abhijin Adiga, Madhav Marathe, S. S. Ravi, Ravi Tandon, Anil Vullikanti
AAAI 2026technical

Estimating the true prevalence of an epidemic outbreak is a key public health problem. This is challenging because surveillance is usually resource intensive and biased. In the network setting, prior work on cost sensitive disease surveillance has focused on choosing a subset of individuals (or node

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2026

Towards High Resolution Probabilistic Coastal Inundation Forecasting from Sparse Observations

Kazi Ashik Islam, Zakaria Mehrab, Mahantesh M Halappanavar, Henning Mortveit, Katragadda Sridhar, Jon Derek Loftis +2
AAAI 2026technical

Coastal flooding poses increasing threats to communities worldwide, necessitating accurate and hyper-local inundation forecasting for effective emergency response. However, real-world deployment of forecasting systems is often constrained by sparse sensor networks, where only a limited subset of loc

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2025

IRRISIGHT: A Large-Scale Multimodal Dataset and Scalable Pipeline to Address Irrigation and Water Management in Agriculture

Nibir Chandra Mandal, Oishee Bintey Hoque, Mandy L Wilson, Samarth Swarup, Sayjro K Nouwakpo, Abhijin Adiga +1
NeurIPS 2025poster

The lack of fine-grained, large-scale datasets on water availability presents a critical barrier to applying machine learning (ML) for agricultural water management. Since there are multiple natural and anthropogenic factors that influence water availability, incorporating diverse multimodal feature…

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2025

Knowledge-Informed Deep Learning for Irrigation Type Mapping from Remote Sensing

Oishee Bintey Hoque, Nibir Chandra Mandal, Abhijin Adiga, Samarth Swarup, Sayjro Kossi Nouwakpo, Amanda Wilson +1
IJCAI 2025

Accurate mapping of irrigation methods is crucial for sustainable agricultural practices and food systems. However, existing models that rely solely on spectral features from satellite imagery are ineffective due to the complexity of agricultural landscapes and limited training data, making this a c

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2024

Efficient PAC Learnability of Dynamical Systems Over Multilayer Networks

Zirou Qiu, Abhijin Adiga, Madhav Marathe, S. S. Ravi, Daniel Rosenkrantz, Richard Stearns +1
ICML 2024poster

Networked dynamical systems are widely used as formal models of real-world cascading phenomena, such as the spread of diseases and information. Prior research has addressed the problem of learning the behavior of an unknown dynamical system when the underlying network has a single layer. In this wor…

Cited by 2Source ↗PDF ↗Scholar ↗
2023

Efficient and Equitable Deployment of Mobile Vaccine Distribution Centers

Da Qi Chen, Ann Li, George Z. Li, Madhav Marathe, Aravind Srinivasan, Leonidas Tsepenekas +1
IJCAI 2023poster

Vaccines have proven to be extremely effective in preventing the spread of COVID-19 and potentially ending the pandemic. Lack of access caused many people not getting vaccinated early, so states such as Virginia deployed mobile vaccination sites in order to distribute vaccines across the state. Here…

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2023

Simulation-Assisted Optimization for Large-Scale Evacuation Planning with Congestion-Dependent Delays

Kazi Ashik Islam, Da Qi Chen, Madhav Marathe, Henning Mortveit, Samarth Swarup, Anil Vullikanti
IJCAI 2023poster

Evacuation planning is a crucial part of disaster management. However, joint optimization of its two essential components, routing and scheduling, with objectives such as minimizing average evacuation time or evacuation completion time, is a computationally hard problem. To approach it, we present M…

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2022

A Reliability-aware Distributed Framework to Schedule Residential Charging of Electric Vehicles

Rounak Meyur, Swapna Thorve, Madhav Marathe, Anil Vullikanti, Samarth Swarup, Henning Mortveit
IJCAI 2022poster

Residential consumers have become active participants in the power distribution network after being equipped with residential EV charging provisions. This creates a challenge for the network operator tasked with dispatching electric power to the residential consumers through the existing distributio…

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2022

Efficiently Learning the Topology and Behavior of a Networked Dynamical System Via Active Queries

Daniel J Rosenkrantz, Abhijin Adiga, Madhav Marathe, Zirou Qiu, S S Ravi, Richard Stearns +1
ICML 2022spotlight

Using a discrete dynamical system model, many papers have addressed the problem of learning the behavior (i.e., the local function at each node) of a networked system through active queries, assuming that the network topology is known. We address the problem of inferring both the topology of the net…

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2022

Finding Nontrivial Minimum Fixed Points in Discrete Dynamical Systems: Complexity, Special Case Algorithms and Heuristics

Zirou Qiu, Chen Chen, Madhav Marathe, S.S. Ravi, Daniel J. Rosenkrantz, Richard Stearns +1
AAAI 2022technical

Networked discrete dynamical systems are often used to model the spread of contagions and decision-making by agents in coordination games. Fixed points of such dynamical systems represent configurations to which the system converges. In the dissemination of undesirable contagions (such as rumors and…

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2021

Synchronous Dynamical Systems on Directed Acyclic Graphs: Complexity and Algorithms

Daniel J. Rosenkrantz, Madhav Marathe, S. S. Ravi, Richard E. Stearns
AAAI 2021technical

Discrete dynamical systems serve as useful formal models to study diffusion phenomena in social networks. Motivated by applications in systems biology, several recent papers have studied algorithmic and complexity aspects of diffusion problems for dynamical systems whose underlying graphs are direc…

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2020

Wisdom of the Ensemble: Improving Consistency of Deep Learning Models

Lijing Wang, Dipanjan Ghosh, Maria Gonzalez Diaz, Ahmed Farahat, Mahbubul Alam, Chetan Gupta +2
NeurIPS 2020poster

Deep learning classifiers are assisting humans in making decisions and hence the user's trust in these models is of paramount importance. Trust is often a function of constant behavior. From an AI model perspective it means given the same input the user would expect the same output, especially for c…

Cited by 16Source ↗PDF ↗code ↗Scholar ↗
2019

PAC Learnability of Node Functions in Networked Dynamical Systems

Abhijin Adiga, Chris J Kuhlman, Madhav Marathe, S Ravi, Anil Vullikanti
ICML 2019oral

We consider the PAC learnability of the local functions at the vertices of a discrete networked dynamical system, assuming that the underlying network is known. Our focus is on the learnability of threshold functions. We show that several variants of threshold functions are PAC learnable and provide…

Cited by 12Source ↗PDF ↗Scholar ↗