Alok N. Choudhary

Materials Chemistry · 2003–2021

A researcher in the Science corpus: 16 papers; trusts 123 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

Materials Chemistry — 170 citations into it; #3,187 of 11,513 by trust here, #2,854 by citations
Artificial Intelligence — 95 citations into it; #17,297 of 35,345 by trust here, #12,974 by citations
Computer Vision and Pattern Recognition — 74 citations into it; #18,049 of 21,575 by trust here, #6,542 by citations
Computational Theory and Mathematics — 67 citations into it; #3,031 of 12,182 by trust here, #1,700 by citations
Electrical and Electronic Engineering — 30 citations into it
Model Architectures — 30 citations into it
Inorganic Chemistry — 29 citations into it
Information Systems — 21 citations into it; #1,847 of 8,771 by trust here, #6,195 by citations

Whom Alok N. Choudhary trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

Who trusts Alok N. Choudhary overall

Papers from Alok N. Choudhary's perspective

Ordered by how strongly the researchers Alok N. Choudhary trusts endorse each paper. Same corpus, a different order for every researcher.

Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
ImageNet classification with deep convolutional neural networks
Gradient-based learning applied to document recognition
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Long Short-Term Memory
Attention is All you Need (Neural Information Processing Systems)
ImageNet: A large-scale hierarchical image database
Going deeper with convolutions
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Learning Multiple Layers of Features from Tiny Images

Their papers

An Exploration of Parameter Redundancy in Deep Networks with Circulant Projections (2015) — 341 citations
Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science (2016) — 1,189 citations
A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials (2016) — 1,611 citations
Combinatorial screening for new materials in unconstrained composition space with machine learning (2014) — 576 citations
Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations (2017) — 297 citations
Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets (2018) — 343 citations
ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition (2018) — 460 citations
Establishing structure-property localization linkages for elastic deformation of three-dimensional high contrast composites using deep learning approaches (2019) — 170 citations
A Two-Phase Algorithm for Fast Discovery of High Utility Itemsets (2005) — 715 citations
A fast high utility itemsets mining algorithm (2005) — 504 citations
Firefly: illuminating future network-on-chip with nanophotonics (2009) — 429 citations
Recent advances and applications of deep learning methods in materials science (2021) — 995 citations
Deep Convolutional Neural Networks with transfer learning for computer vision-based data-driven pavement distress detection (2017) — 900 citations
Toward enhanced understanding and projections of climate extremes using physics-guided data mining techniques (2014)
The International Exascale Software Project roadmap (2011) — 769 citations
Parallel netCDF: A High-Performance Scientific I/O Interface (2003) — 477 citations