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Engineering

Engineering Paper Reviews

AI-generated reviews of key Engineering papers, structured into motivation, method, and results.

All Computer Science Mathematics Physics and Astronomy Engineering Materials Science Chemistry Chemical Engineering Earth and Planetary Sciences Environmental Science Energy Biochemistry, Genetics and Molecular Biology Neuroscience Immunology and Microbiology Agricultural and Biological Sciences Medicine Pharmacology, Toxicology and Pharmaceutics Health Professions Economics, Econometrics and Finance Business, Management and Accounting Decision Sciences Social Sciences Psychology Arts and Humanities

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9999+ results

Classification based Grasp Detection using Spatial Transformer Network

Dongwon Park, Se Young Chun

arXiv (Cornell University)|2018|32 citations

Comment on the paper "Dark matter searches going bananas: the contribution of Potassium (and Chlorine) to the 3.5 keV line" by T. Jeltema and S. Profumo

Alexey Boyarsky, J. Franse, +2

arXiv (Cornell University)|2014|32 citations

Compressed Sensing of Simultaneous Low-Rank and Joint-Sparse Matrices

Mohammad Golbabaee, Pierre Vandergheynst

arXiv (Cornell University)|2012|32 citations

Computational Limits for Matrix Completion

Moritz Hardt, Raghu Meka, +2

arXiv (Cornell University)|2014|32 citations

David Hilbert and the origin of the "Schwarzschild solution"

ArXiv.org|2003|32 citations

Decomposing Linearly Constrained Nonconvex Problems by a Proximal Primal Dual Approach: Algorithms, Convergence, and Applications

arXiv (Cornell University)|2016|32 citations

Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safety

Jianyu Chen, Bodi Yuan, +1

arXiv (Cornell University)|2019|32 citations

Deep Reinforcement Learning for Six Degree-of-Freedom Planetary Powered Descent and Landing

Brian Gaudet, Richard Linares, +1

arXiv (Cornell University)|2018|32 citations

DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing

Yongcheng Liu, Bin Fan, +4

arXiv (Cornell University)|2019|32 citations

Direct data-driven forecast of local turbulent heat flux in Rayleigh-B\'{e}nard convection

Sandeep Pandey, Philipp Teutsch, +2

arXiv (Cornell University)|2022|32 citations

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