activity
20142023
most citedCrop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning

226 citations · 729 across the 62 of their papers we have counts for

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10 papers · 1 filter

stat.ML2018★ 2 cited

Root-cause Analysis for Time-series Anomalies via Spatiotemporal Graphical Modeling in Distributed Complex Systems

Chao Liu, Kin Gwn Lore, Zhanhong Jiang +1

Performance monitoring, anomaly detection, and root-cause analysis in complex cyber-physical systems (CPSs) are often highly intractable due to widely diverse operational modes, di…

stat.ML2018★ 5 cited

On Consensus-Optimality Trade-offs in Collaborative Deep Learning

Zhanhong Jiang, Aditya Balu, Chinmay Hegde +1

In distributed machine learning, where agents collaboratively learn from diverse private data sets, there is a fundamental tension between consensus and optimality. In this paper,…

stat.ML2018★ 51 cited

Predicting County Level Corn Yields Using Deep Long Short Term Memory Models

Zehui Jiang, Chao Liu, Nathan P. Hendricks +3

Corn yield prediction is beneficial as it provides valuable information about production and prices prior the harvest. Publicly available high-quality corn yield prediction can hel…

stat.ML2017★ 6 cited

A Forward-Backward Approach for Visualizing Information Flow in Deep Networks

Aditya Balu, Thanh V. Nguyen, Apurva Kokate +2

We introduce a new, systematic framework for visualizing information flow in deep networks. Specifically, given any trained deep convolutional network model and a given test image,…

stat.ML2017★ 4 cited

Learning and Visualizing Localized Geometric Features Using 3D-CNN: An Application to Manufacturability Analysis of Drilled Holes

Sambit Ghadai, Aditya Balu, Adarsh Krishnamurthy +1

3D Convolutional Neural Networks (3D-CNN) have been used for object recognition based on the voxelized shape of an object. However, interpreting the decision making process of thes…

stat.ML2017★ 1 cited

Interpretable Deep Learning applied to Plant Stress Phenotyping

Sambuddha Ghosal, David Blystone, Asheesh K. Singh +3

Availability of an explainable deep learning model that can be applied to practical real world scenarios and in turn, can consistently, rapidly and accurately identify specific and…

stat.ML2017★ 77 cited

Collaborative Deep Learning in Fixed Topology Networks

Zhanhong Jiang, Aditya Balu, Chinmay Hegde +1

There is significant recent interest to parallelize deep learning algorithms in order to handle the enormous growth in data and model sizes. While most advances focus on model para…

stat.ML2017★ 1 cited

A Machine-Learning Framework for Design for Manufacturability

Aditya Balu, Sambit Ghadai, Gavin Young +2

this is a duplicate submission(original is arXiv:1612.02141). Hence want to withdraw it

stat.ML2017

Hierarchical Symbolic Dynamic Filtering of Streaming Non-stationary Time Series Data

Adedotun Akintayo, Soumik Sarkar

This paper proposes a hierarchical feature extractor for non-stationary streaming time series based on the concept of switching observable Markov chain models. The slow time-scale…

stat.ML2017★ 2 cited

Energy Prediction using Spatiotemporal Pattern Networks

Zhanhong Jiang, Chao Liu, Adedotun Akintayo +2

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dy…