
NURBSDiff: A Differentiable NURBS Layer for Machine Learning CAD Applications
Recent deeplearningbased techniques for the reconstruction of geometri...
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Distributed Multigrid Neural Solvers on Megavoxel Domains
We consider the distributed training of largescale neural networks that...
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Granger Causality Based Hierarchical Time Series Clustering for State Estimation
Clustering is an unsupervised learning technique that is useful when wor...
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Sugar and Stops in Drivers with InsulinDependent Type 1 Diabetes
Diabetes is a major public health challenge worldwide. Abnormal physiolo...
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CrossGradient Aggregation for Decentralized Learning from NonIID data
Decentralized learning enables a group of collaborative agents to learn ...
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A modular vision language navigation and manipulation framework for long horizon compositional tasks in indoor environment
In this paper we propose a new framework  MoViLan (Modular Vision and L...
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3D Convolutional Selective Autoencoder For Instability Detection in Combustion Systems
While analytical solutions of critical (phase) transitions in physical s...
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Physicsconsistent deep learning for structural topology optimization
Topology optimization has emerged as a popular approach to refine a comp...
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Deep Multiview Image Fusion for Soybean Yield Estimation in Breeding Applications Deep Multiview Image Fusion for Soybean Yield Estimation in Breeding Applications
Reliable seed yield estimation is an indispensable step in plant breedin...
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Querybased Targeted ActionSpace Adversarial Policies on Deep Reinforcement Learning Agents
Advances in computing resources have resulted in the increasing complexi...
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Decentralized Deep Learning using MomentumAccelerated Consensus
We consider the problem of decentralized deep learning where multiple ag...
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Few shot clustering for indoor occupancy detection with extremely lowquality images from battery free cameras
Reliable detection of human occupancy in indoor environments is critical...
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Spatiotemporal Attention for Multivariate Time Series Prediction and Interpretation
Multivariate time series modeling and prediction problems are abundant i...
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Deep Generative Models that Solve PDEs: Distributed Computing for Training Large DataFree Models
Recent progress in scientific machine learning (SciML) has opened up the...
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Robustifying Reinforcement Learning Agents via Action Space Adversarial Training
Adoption of machine learning (ML)enabled cyberphysical systems (CPS) a...
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Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning
Accurate prediction of crop yield supported by scientific and domainrel...
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How useful is Active Learning for Imagebased Plant Phenotyping?
Deep learning models have been successfully deployed for a diverse array...
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Deep Reinforcement Learning for Adaptive Traffic Signal Control
Many existing traffic signal controllers are either simple adaptive cont...
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A perspective on multiagent communication for information fusion
Collaborative decision making in multiagent systems typically requires ...
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A SaddlePoint Dynamical System Approach for Robust Deep Learning
We propose a novel discretetime dynamical systembased framework for ac...
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On Higherorder Moments in Adam
In this paper, we investigate the popular deep learning optimization rou...
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Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents
Robustness of Deep Reinforcement Learning (DRL) algorithms towards adver...
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Learning to Cope with Adversarial Attacks
The security of Deep Reinforcement Learning (Deep RL) algorithms deploye...
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Encoding Invariances in Deep Generative Models
Reliable training of generative adversarial networks (GANs) typically re...
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Driver Behavior Analysis Using Lane Departure Detection Under Challenging Conditions
In this paper, we present a novel model to detect lane regions and extra...
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Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers
Deep neural networks have been shown to exhibit an intriguing vulnerabil...
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Flow Shape Design for Microfluidic Devices Using Deep Reinforcement Learning
Microfluidic devices are utilized to control and direct flow behavior in...
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3D Deep Learning with voxelized atomic configurations for modeling atomistic potentials in complex solidsolution alloys
The need for advanced materials has led to the development of complex, m...
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Physicsaware Deep Generative Models for Creating Synthetic Microstructures
A key problem in computational material science deals with understanding...
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Interpretable deep learning for guided structureproperty explorations in photovoltaics
The performance of an organic photovoltaic device is intricately connect...
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Online Robust Policy Learning in the Presence of Unknown Adversaries
The growing prospect of deep reinforcement learning (DRL) being used in ...
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Rootcause Analysis for Timeseries Anomalies via Spatiotemporal Graphical Modeling in Distributed Complex Systems
Performance monitoring, anomaly detection, and rootcause analysis in co...
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MultiResolution 3D Convolutional Neural Networks for Object Recognition
Learning from 3D Data is a fascinating idea which is well explored and s...
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On ConsensusOptimality Tradeoffs in Collaborative Deep Learning
In distributed machine learning, where agents collaboratively learn from...
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Predicting County Level Corn Yields Using Deep Long Short Term Memory Models
Corn yield prediction is beneficial as it provides valuable information ...
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Explaining hyperspectral imaging based plant disease identification: 3D CNN and saliency maps
Our overarching goal is to develop an accurate and explainable model for...
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A ForwardBackward Approach for Visualizing Information Flow in Deep Networks
We introduce a new, systematic framework for visualizing information flo...
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Learning and Visualizing Localized Geometric Features Using 3DCNN: An Application to Manufacturability Analysis of Drilled Holes
3D Convolutional Neural Networks (3DCNN) have been used for object reco...
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Interpretable Deep Learning applied to Plant Stress Phenotyping
Availability of an explainable deep learning model that can be applied t...
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Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean
Charcoal rot is a fungal disease that thrives in warm dry conditions and...
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Collaborative Deep Learning in Fixed Topology Networks
There is significant recent interest to parallelize deep learning algori...
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A MachineLearning Framework for Design for Manufacturability
this is a duplicate submission(original is arXiv:1612.02141). Hence want...
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Hierarchical Symbolic Dynamic Filtering of Streaming Nonstationary Time Series Data
This paper proposes a hierarchical feature extractor for nonstationary ...
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Energy Prediction using Spatiotemporal Pattern Networks
This paper presents a novel datadriven technique based on the spatiotem...
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Learning Localized Geometric Features Using 3DCNN: An Application to Manufacturability Analysis of Drilled Holes
3D convolutional neural networks (3DCNN) have been used for object reco...
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A Bayesian Network approach to CountyLevel Corn Yield Prediction using historical data and expert knowledge
Crop yield forecasting is the methodology of predicting crop yields prio...
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Deep Action Sequence Learning for Causal Shape Transformation
Deep learning became the method of choice in recent year for solving a w...
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Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders on Hispeed Flame Video
This paper proposes an endtoend convolutional selective autoencoder ap...
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An endtoend convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection
This paper proposes a novel selective autoencoder approach within the fr...
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LLNet: A Deep Autoencoder Approach to Natural Lowlight Image Enhancement
In surveillance, monitoring and tactical reconnaissance, gathering the r...
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Soumik Sarkar
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Assistant Professor at Iowa State University and Partner and Chief Innovation Officer at Etalyc LLC