Jarvis D. Haupt

Computational Mechanics · 2006–2010

A researcher in the Science corpus: 6 papers; trusts 33 researchers and is trusted by 38 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 55 citations into it; #815 of 10,001 by trust here, #948 by citations
• Computer Vision and Pattern Recognition — 26 citations into it
• Computer Networks and Communications — 24 citations into it; #8,293 of 9,886 by trust here, #3,523 by citations
• Electrical and Electronic Engineering — 21 citations into it; #7,090 of 16,539 by trust here, #8,627 by citations
• Applied Mathematics — 18 citations into it; #747 of 7,620 by trust here, #1,522 by citations
• Biomedical Engineering — 17 citations into it; #349 of 10,734 by trust here, #2,462 by citations
• Signal Processing — 14 citations into it
• Aerospace Engineering — 9 citations into it

Whom Jarvis D. Haupt trusts overall

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

1. E.J. Candes
2. Robert D. Nowak
3. Terence Tao
4. Mário A. T. Figueiredo
5. Justin K. Romberg
6. Joel A. Tropp
7. David L. Donoho
8. Ronald A. DeVore
9. Stephen J. Wright
10. Andreas F. Molisch

Who trusts Jarvis D. Haupt overall

1. Marco F. Duarte
2. E.J. Candes
3. Richard Baraniuk
4. Waheed Uz Zaman Bajwa
5. Mário A. T. Figueiredo
6. Robert D. Nowak
7. Francis R. Bach
8. Jonathan Brophy
9. Nam H. Nguyen
10. Sungkwang Mun

Papers from Jarvis D. Haupt's perspective

Ordered by how strongly the researchers Jarvis D. Haupt trusts endorse each paper. Same corpus, a different order for every researcher.

1. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
2. Stable signal recovery from incomplete and inaccurate measurements
3. Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
4. An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
5. Regression Shrinkage and Selection via the Lasso
6. Atomic Decomposition by Basis Pursuit
7. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples (arXiv.org)
8. The Dantzig selector: Statistical estimation when P is much larger than n
9. Compressed Sensing
10. Sparse Reconstruction by Separable Approximation

Their papers

• Signal Reconstruction From Noisy Random Projections (2006) — 670 citations
• Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation (2010) — 437 citations
• Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels (2010) — 1,148 citations
• Compressive wireless sensing (2006) — 373 citations
• Compressed Sensing for Networked Data (2008) — 555 citations
• Toeplitz-Structured Compressed Sensing Matrices (2007) — 341 citations