Rebecca Willett

Q: What Schools Are Affiliated With Rebecca Willett

Rebecca Willett is affiliated with the following schools: Rice University, University of Wisconsin–Madison, University of Chicago, Duke University

Rebecca Willett's AcademicInfluence.com Rankings

Rebecca Willett

Mathematics

#5926

World Rank

#8289

Historical Rank

#1861

USA Rank

Statistics

#819

World Rank

#909

Historical Rank

#180

USA Rank

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Mathematics

Why Is Rebecca Willett Influential?

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According to Wikipedia, Rebecca Willett is an American statistician and computer scientist whose research involves machine learning, signal processing, and data science. She is a professor of statistics and computer science at the University of Chicago.

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Rebecca Willett's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Single disperser design for coded aperture snapshot spectral imaging. (2008) (703)
Single-shot compressive spectral imaging with a dual-disperser architecture. (2007) (561)
Deep Learning Techniques for Inverse Problems in Imaging (2020) (304)
Poisson Noise Reduction with Non-local PCA (2012) (294)
Platelets: a multiscale approach for recovering edges and surfaces in photon-limited medical imaging (2003) (279)
This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms—Theory and Practice (2010) (263)
Backcasting: adaptive sampling for sensor networks (2004) (255)
Compressed sensing for practical optical imaging systems: A tutorial (2011) (234)
Online Convex Optimization in Dynamic Environments (2015) (179)
Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection (2014) (168)
Compressed Sensing Performance Bounds Under Poisson Noise (2009) (157)
Faster Rates in Regression via Active Learning (2005) (153)
Estimating inhomogeneous fields using wireless sensor networks (2004) (142)
Multiscale Poisson Intensity and Density Estimation (2007) (142)
Compressive coded aperture superresolution image reconstruction (2008) (112)
Change-Point Detection for High-Dimensional Time Series With Missing Data (2012) (112)
Compressive coded aperture video reconstruction (2008) (106)
Compressive coded aperture imaging (2009) (102)
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case (2019) (97)
Multi-excitation Raman spectroscopy technique for fluorescence rejection. (2008) (96)
Dynamical Models and tracking regret in online convex programming (2013) (96)
Thin infrared imaging systems through multichannel sampling. (2008) (93)
Neumann Networks for Linear Inverse Problems in Imaging (2020) (92)
Scalable Generalized Linear Bandits: Online Computation and Hashing (2017) (86)
Minimax Optimal Level-Set Estimation (2007) (79)
Deep Equilibrium Architectures for Inverse Problems in Imaging (2021) (76)
RADIOACTIVE SCANDIUM IN THE YOUNGEST GALACTIC SUPERNOVA REMNANT G1.9+0.3 (2010) (61)
Improved Strongly Adaptive Online Learning using Coin Betting (2016) (61)
Sequential Anomaly Detection in the Presence of Noise and Limited Feedback (2009) (60)
Engineering induction of singular neural rosette emergence within hPSC-derived tissues (2018) (57)
NONUNIFORM EXPANSION OF THE YOUNGEST GALACTIC SUPERNOVA REMNANT G1.9+0.3 (2009) (54)
Performance Bounds for Expander-Based Compressed Sensing in Poisson Noise (2010) (54)
Tracking Dynamic Point Processes on Networks (2014) (53)
Hypergraph-Based Anomaly Detection of High-Dimensional Co-Occurrences (2009) (53)
Fast multiresolution photon-limited image reconstruction (2004) (53)
Multiscale reconstruction for computational spectral imaging (2007) (49)
Algebraic Variety Models for High-Rank Matrix Completion (2017) (48)
Online Markov Decision Processes With Kullback–Leibler Control Cost (2014) (47)
Sparse poisson intensity reconstruction algorithms (2009) (43)
An Optimal Statistical and Computational Framework for Generalized Tensor Estimation (2020) (43)
Matrix Completion Under Monotonic Single Index Models (2015) (40)
Multiscale Analysis of Photon-Limited Astronomical Images (2007) (39)
Group-sparse subspace clustering with missing data (2016) (38)
Inference of High-dimensional Autoregressive Generalized Linear Models (2016) (37)
Bilinear Bandits with Low-rank Structure (2019) (37)
PMU-Based Detection of Imbalance in Three-Phase Power Systems (2014) (36)
Decentralized Online Convex Programming with local information (2011) (36)
Minimax Optimal Rates for Poisson Inverse Problems With Physical Constraints (2014) (34)
Wavelet-based superresolution in astronomy. (2003) (31)
Oracle Inequalities and Minimax Rates for Nonlocal Means and Related Adaptive Kernel-Based Methods (2011) (30)
SUPERNOVA EJECTA IN THE YOUNGEST GALACTIC SUPERNOVA REMNANT G1.9+0.3 (2013) (29)
Poisson image reconstruction with total variation regularization (2010) (28)
Learning Single Index Models in High Dimensions (2015) (28)
Online Optimization in Dynamic Environments (2013) (27)
Network Estimation From Point Process Data (2018) (27)
Toward a Model for Source Addresses of Internet Background Radiation (2006) (26)
Multiscale Photon-Limited Spectral Image Reconstruction (2010) (26)
Compressive Optical Imaging: Architectures and Algorithms (2011) (26)
Model Adaptation for Inverse Problems in Imaging (2020) (25)
EXPANSION OF THE YOUNGEST GALACTIC SUPERNOVA REMNANT G1.9+0.3 (2017) (25)
SPIRAL out of convexity: sparsity-regularized algorithms for photon-limited imaging (2010) (24)
Reducing Basis Mismatch in Harmonic Signal Recovery via Alternating Convex Search (2014) (23)
Coarse-to-fine manifold learning (2004) (23)
Rapid staining and imaging of subnuclear features to differentiate between malignant and benign breast tissues at a point-of-care setting (2016) (23)
A Data-Dependent Weighted LASSO Under Poisson Noise (2015) (22)
Neumann Networks for Inverse Problems in Imaging (2019) (22)
GRAPH-BASED REGULARIZATION FOR REGRESSION PROBLEMS WITH HIGHLY-CORRELATED DESIGNS (2018) (21)
Approach to simultaneously denoise and invert backscatter and extinction from photon-limited atmospheric lidar observations. (2016) (21)
Statistically and Computationally Efficient Change Point Localization in Regression Settings (2019) (21)
Localizing Changes in High-Dimensional Vector Autoregressive Processes (2019) (20)
Hyperspectral target detection from incoherent projections (2010) (20)
Ultra-thin multiple-channel LWIR imaging systems (2006) (18)
Proximal-Gradient methods for poisson image reconstruction with BM3D-Based regularization (2017) (18)
Learning High-Dimensional Generalized Linear Autoregressive Models (2019) (18)
Detection of anomalous meetings in a social network (2008) (18)
Compressive coded apertures for high-resolution imaging (2010) (18)
Online Markov decision processes with Kullback-Leibler control cost (2012) (17)
Quantitative Segmentation of Fluorescence Microscopy Images of Heterogeneous Tissue: Application to the Detection of Residual Disease in Tumor Margins (2013) (17)
Hyperspectral target detection from incoherent projections: Nonequiprobable targets and inhomogeneous SNR (2010) (17)
Spatio-temporal Compressed Sensing with Coded Apertures and Keyed Exposures (2011) (17)
Sparsity-regularized photon-limited imaging (2010) (17)
A two-stage denoising filter: The preprocessed Yaroslavsky filter (2012) (17)
Performance bounds on compressed sensing with Poisson noise (2009) (16)
Gradient projection for linearly constrained convex optimization in sparse signal recovery (2010) (16)
Sparsity and Structure in Hyperspectral Imaging (2014) (15)
Superimposed video disambiguation for increased field of view. (2008) (15)
Localizing Changes in High-Dimensional Regression Models (2020) (14)
Online anomaly detection with expert system feedback in social networks (2011) (14)
Coarse-to-fine manifold learning [image processing example] (2004) (14)
Minimax optimal level set estimation (2005) (14)
Online Learning for Changing Environments using Coin Betting (2017) (14)
Target detection performance bounds in compressive imaging (2011) (13)
Sequential probability assignment via online convex programming using exponential families (2009) (12)
Tensor Methods for Nonlinear Matrix Completion (2018) (12)
On Learning High Dimensional Structured Single Index Models (2016) (12)
Sparse linear contextual bandits via relevance vector machines (2017) (12)
Low algebraic dimension matrix completion (2017) (12)
Hypergraph-Based Anomaly Detection in Very Large Networks (2008) (12)
Logarithmic total variation regularization for cross-validation in photon-limited imaging (2013) (11)
Performance bounds for expander-based compressed sensing in the presence of Poisson noise (2009) (11)
Structured Illumination Microscopy and a Quantitative Image Analysis for the Detection of Positive Margins in a Pre-Clinical Genetically Engineered Mouse Model of Sarcoma (2016) (11)
Dynamic relational topic model for social network analysis with noisy links (2011) (11)
A quantitative microscopic approach to predict local recurrence based on in vivo intraoperative imaging of sarcoma tumor margins (2015) (10)
Coded-aperture Raman imaging for standoff explosive detection (2012) (10)
Controlling the error in FMRI: Hypothesis testing or set estimation? (2008) (10)
Multiscale online tracking of manifolds (2012) (10)
Graph Signal Processing: Foundations and Emerging Directions (2020) (10)
Online logistic regression on manifolds (2013) (10)
The false discovery rate for statistical pattern recognition (2009) (10)
Graph-Based Regularization for Regression Problems with Alignment and Highly Correlated Designs (2018) (10)
Mixture regression as subspace clustering (2017) (9)
Leveraging spatial textures, through machine learning, to identify aerosols and distinct cloud types from multispectral observations (2020) (9)
Fast, near-optimal, multiresolution estimation of poisson signals and images (2004) (9)
Multiscale Density Estimation (2003) (9)
Predicting kernel processing score of harvested and processed corn silage via image processing techniques (2019) (9)
Auto-differentiable Ensemble Kalman Filters (2021) (9)
To e or not to e in poisson image reconstruction (2014) (9)
Online Data Thinning via Multi-Subspace Tracking (2016) (9)
Errata : Sampling Trajectories for Sparse Image Recovery (2011) (9)
CORT: classification or regression trees (2003) (8)
Backcasting : A New Approach to Energy Conservation in Sensor Networks (2003) (8)
Multiscale Reconstruction for Photon-Limited Shifted Excitation Raman Spectroscopy (2007) (8)
Fast disambiguation of superimposed images for increased field of view (2008) (8)
Learned Patch-Based Regularization for Inverse Problems in Imaging (2019) (8)
Fishing in Poisson streams: Focusing on the whales, ignoring the minnows (2010) (7)
SPARSE SUBSPACE CLUSTERING WITH MISSING AND CORRUPTED DATA (2018) (7)
Graph-Guided Regularized Regression of Pacific Ocean Climate Variables to Increase Predictive Skill of Southwestern U.S. Winter Precipitation. (2020) (7)
Regularized Non-Gaussian Image Denoising (2015) (7)
Tissue quantification in photon-limited microendoscopy (2011) (7)
Subspace Clustering with Missing and Corrupted Data (2017) (7)
Detecting Abrupt Changes in High-Dimensional Self-Exciting Poisson Processes (2020) (7)
Multiscale Intensity Estimation for Marked Poisson Processes (2007) (7)
Complexity-regularized multiresolution density estimation (2004) (7)
Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors] (2020) (7)
Online learning of neural network structure from spike trains (2015) (7)
Functional Linear Regression with Mixed Predictors. (2020) (7)
Single disperser design for compressive, single-snapshot spectral imaging (2007) (7)
From minimax value to low-regret algorithms for online Markov decision processes (2014) (6)
Multiscale Reconstruction of Photon-Limited Hyperspectral Data (2007) (6)
Level set estimation in medical imaging (2005) (6)
Pure Exploration in Kernel and Neural Bandits (2021) (6)
Compressive Coded Aperture Keyed Exposure Imaging with Optical Flow Reconstruction (2013) (6)
Level set estimation via trees [signal processing applications] (2005) (6)
Data-Driven Cloud Clustering via a Rotationally Invariant Autoencoder (2021) (6)
Adaptive sampling for wireless sensor networks (2004) (5)
Subspace Clustering via Tangent Cones (2017) (5)
Sparse Linear Regression With Missing Data (2015) (5)
Algorithms for differentiating between images of heterogeneous tissue across fluorescence microscopes. (2016) (5)
Multiresolution nonparametric intensity and density estimation (2002) (5)
Multiscale likelihood analysis and image reconstruction (2003) (5)
Time-evolving modeling of social networks (2011) (4)
Adaptive Differentially Private Empirical Risk Minimization (2021) (4)
Missing Data in Sparse Transition Matrix Estimation for Sub-Gaussian Vector Autoregressive Processes (2018) (4)
Functional Autoregressive Processes in Reproducing Kernel Hilbert Spaces (2020) (4)
Motion-adaptive compressive coded apertures (2011) (4)
The Role of Linear Layers in Nonlinear Interpolating Networks (2022) (4)
Approximated Bayesian Inference for Massive Streaming Data (2013) (4)
A recursive procedure for density estimation on the binary hypercube (2011) (4)
Foreground and background reconstruction in poisson video (2013) (4)
Platelets for multiscale analysis in photon-limited imaging (2002) (4)
Generalization Error Analysis for FDR Controlled Classification (2007) (4)
POISSON COMPRESSED SENSING (2011) (4)
Detection and Description of Change in Visual Streams (2020) (3)
Estimating Network Structure from Incomplete Event Data (2018) (3)
Network estimation via poisson autoregressive models (2017) (3)
Fixing basis mismatch in compressively sampled photonic link (2014) (3)
Leveraging spatial textures, through machine learning, to identify aerosol and distinct cloud types from multispectral observations (2020) (3)
Regret minimization algorithms for single-controller zero-sum stochastic games (2016) (3)
Cloud Classification with Unsupervised Deep Learning (2022) (3)
Smooth sampling trajectories for sparse recovery in MRI (2011) (3)
Inferring high-dimensional poisson autoregressive models (2016) (3)
Short and smooth sampling trajectories for compressed sensing (2011) (3)
Level Set Estimation from Projection Measurements: Performance Guarantees and Fast Computation (2012) (2)
Target Detection Performance Bounds in Compressive Spectral Imaging (2011) (2)
Multiresolution methods for recovering signals and sets from noisy observations (2005) (2)
Relax but stay in control: from value to algorithms for online Markov decision processes (2013) (2)
MULTISCALE INTENSITY ESTIMATION FOR MULTI-PHOTON MICROSCOPY (2007) (2)
Multiscale Analysis of Photon-Limited Astronomical Signals and Images (2002) (2)
Multiscale analysis for intensity and density estimation (2002) (2)
Model Adaptation In Biomedical Image Reconstruction (2021) (2)
Fast level set estimation from projection measurements (2011) (2)
Developing Unsupervised Learning Models for Cloud Classification (2019) (2)
Asymmetric Expansion of the Youngest Galactic Supernova Remnant G1.9+0.3 (2017) (2)
Optical designs for compressive single shot spectral imaging (2007) (2)
A Snap-shot Dual-disperser Imager for Compressive Hyperspectral Imaging (2007) (1)
Compressive Spectral Imaging and Multiscale Reconstruction Methods (2007) (1)
Online optimization in parametric dynamic environments (2013) (1)
Integrated Sensing and Information Processing Theme-Based Redesign of the Undergraduate Electrical and Computer Engineering Curriculum at Duke University. (2011) (1)
Integrating Sensing and Information Processing in an Electrical and Computer Engineering undergraduate curriculum (2009) (1)
Signal representations in modern signal processing (2017) (1)
A New Approach to Inverting Backscatter and Extinction from Photon-Limited Lidar Observations (2016) (1)
Coded-excitation Raman spectroscopy for ethanol chemometrics of tissue (2006) (1)
Target detection performance bounds in compressive imaging (2012) (1)
Cloud Characterization With Deep Learning II (2018) (1)
Reduced-Order Autodifferentiable Ensemble Kalman Filters (2023) (1)
Dual-scale masks for spatio-temporal compressive imaging (2013) (1)
Supernova Ejecta in G1.9+0.3: Thermal Emission and Radioactive Decay (2010) (1)
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction (2022) (1)
Poisson Noise Reduction with Non-local PCA (2013) (1)
The value of multispectral observations in photon-limited quantitative tissue analysis (2012) (1)
Learning to Solve Linear Inverse Problems in Imaging with Neumann Networks (2019) (1)
Prediction in the Presence of Response-Dependent Missing Labels (2021) (0)
Density Estimation and Anomaly Detection in Large Social Networks (2014) (0)
Image reconstruction of multiphoton microscopy data (2009) (0)
Denoising Methods with Applications to Microscopy (2019) (0)
Lazy Estimation of Variable Importance for Large Neural Networks (2022) (0)
Spectral Target and Anomaly Detection from Incoherent Projections (0)
Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting (2022) (0)
Context-dependent Networks in Multivariate Time Series: Models, Methods, and Risk Bounds in High Dimensions (2021) (0)
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification (2022) (0)
Session WA1: Sparse representations and compressive sensing (2009) (0)
Machine learning for inverse problems (Conference Presentation) (2022) (0)
Quantitative segmentation of fluorescence microscopy images of heterogeneous tissue: Approach for tuning algorithm parameters (2013) (0)
Assessing kernel processing score of harvested corn silage in real-time using image analysis and machine learning (2022) (0)
Genomic transcription regulatory element location analysis via poisson weighted lasso (2016) (0)
Cloud Clustering Over January 2003 via Scalable Rotationally Invariant Autoencoder (2021) (0)
C LOUD C LASSIFICATION WITH U NSUPERVISED D EEP L EARNING (2019) (0)
Composite Hypotheses and Generalized Likelihood Ratio Tests (2016) (0)
Heavy-Element Ejecta in G1.9+0.3 (2013) (0)
Engineering Perspectives on AI (2019) (0)
Guest Editorial (2020) (0)
New Understanding of Cloud Processes via Unsupervised Cloud Classification in Satellite Images (2021) (0)
Sparse Transition Matrix Estimation for Sub-Gaussian Autoregressive Processes with Missing Data (2018) (0)
MULTISCALEINTENSITYESTIMATIONFOR MARKED POISSONPROCESSES (2007) (0)
Learning to Regularize Using Neumann Networks (2019) (0)
Decision making with uncertainty (2017) (0)
Bagging Provides Assumption-free Stability (2023) (0)
Sequential Prediction for Information Fusion and Control (2013) (0)
t-tests and p-values (2016) (0)
Analytic Sensing : Localization of ( Sparse ) Sources using FRI 11 : 45 – 12 : 15 (2010) (0)
Atmospheric lidar imaging and poisson inverse problems (2016) (0)
Near-minimax recursive density estimation on the binary hypercube (2008) (0)
Response to Jordan (2019) (0)
Compressive Optical Imaging Systems -- Theory, Devices and Implementation (2009) (0)
Thinning for High Volume Streaming Data (2017) (0)
Radioactivity, Particle Acceleration, And Supernova Ejecta In The Youngest Galactic SNR G1.9+0.3 (2011) (0)
Multiresolution Intensity Estimation of Piecewise Linear Poisson Processes (2001) (0)
Photon-limited Sensing and Surveillance (2015) (0)
Context-dependent self-exciting point processes: models, methods, and risk bounds in high dimensions (2020) (0)
Social Network Analysis : Online Anomaly Detection and Graphical Model Selection (2011) (0)
Coded-Excitation Raman Spectroscopy for Raman Signal Estimation in Highly Fluorescent Media (2007) (0)
MULTISCALERECONSTRUCTIONFOR PHOTON-LIMITEDSHIFTEDEXCITATION RAMAN SPECTROSCOPY (2007) (0)
Minimax risk for Poisson compressed sensing (2009) (0)
Ultra-Thin Multi-Aperture LWIR Imagers (2006) (0)

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Other Resources About Rebecca Willett

en.wikipedia.org

What Schools Are Affiliated With Rebecca Willett?

Rebecca Willett is affiliated with the following schools: