Kaushik Bhattacharya

Artificial Intelligence · 2000–2023

A researcher in the Science corpus: 18 papers; trusts 48 researchers and is trusted by 63 researchers here, as inferred from the citation graph.

Subfields

Artificial Intelligence — 64 citations into it; #16,479 of 35,345 by trust here, #12,761 by citations
Statistical and Nonlinear Physics — 56 citations into it; #982 of 10,127 by trust here, #896 by citations
Materials Chemistry — 47 citations into it; #587 of 11,513 by trust here, #4,939 by citations
Biomedical Engineering — 43 citations into it; #2,151 of 10,734 by trust here, #4,247 by citations
Computer Vision and Pattern Recognition — 37 citations into it
Computational Mechanics — 30 citations into it; #3,100 of 10,001 by trust here, #1,929 by citations
Computational Theory and Mathematics — 20 citations into it
Statistics and Probability — 20 citations into it; #10,077 of 12,932 by trust here, #6,853 by citations

Whom Kaushik Bhattacharya trusts overall

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

Who trusts Kaushik Bhattacharya overall

Papers from Kaushik Bhattacharya's perspective

Ordered by how strongly the researchers Kaushik Bhattacharya 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
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Attention is All you Need (Neural Information Processing Systems)
Gradient-based learning applied to document recognition
Long Short-Term Memory
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Learning Multiple Layers of Features from Tiny Images
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
ImageNet: A large-scale hierarchical image database

Their papers

Multipole Graph Neural Operator for Parametric Partial Differential Equations (2020) — 539 citations
Microstructure of martensite : why it forms and how it gives rise to the shape-memory effect (2003) — 1,016 citations
Model Reduction and Neural Networks for Parametric PDEs (2020) — 476 citations
All-organic dielectric-percolative three-component composite materials with high electromechanical response (2004) — 203 citations
A computational model of ferroelectric domains. Part I: model formulation and domain switching (2005) — 320 citations
Stress-induced martensitic phase transformation in thin sheets of Nitinol (2007) — 213 citations
Domain patterns and macroscopic behaviour of ferroelectric materials (2001) — 169 citations
Effective toughness of heterogeneous media (2014) — 225 citations
Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs (2023) — 1,356 citations
Neural Operator: Learning Maps Between Function Spaces (2021) — 645 citations
Fourier Neural Operator for Parametric Partial Differential Equations (2020) — 4,467 citations
Neural Operator: Graph Kernel Network for Partial Differential Equations (2020) — 1,099 citations
Metamaterials with engineered failure load and stiffness (2019) — 27 citations
Snap-through actuation of thick-wall electroactive balloons (2012) — 150 citations
Gaussian curvature from flat elastica sheets (2011) — 173 citations
Kinetics of phase transformations in the peridynamic formulation of continuum mechanics (2006) — 162 citations
Ferroelectric perovskites for electromechanical actuation (2003) — 145 citations
Large strain electrostrictive actuation in barium titanate (2000) — 145 citations