The curvelet transform for image denoising. - Emmanuel J. Candès (ICIP (1), 2001)

Curvelets and Curvilinear Integrals. - Emmanuel J. Candès; David L. Donoho (J. Approx. Theory, 2001)

Ridgelets and the Representation of Mutilated Sobolev Functions. - Emmanuel J. Candès (SIAM J. Math. Anal., 2001)

New multiscale transforms, minimum total variation synthesis: applications to edge-preserving image reconstruction. - Emmanuel J. Candès; Franck Guo (Signal Process., 2002)

The curvelet transform for image denoising. - Jean-Luc Starck; Emmanuel J. Candès; David L. Donoho (IEEE Trans. Image Process., 2002)

Gray and color image contrast enhancement by the curvelet transform. - Jean-Luc Starck; Fionn Murtagh; Emmanuel J. Candès; David L. Donoho (IEEE Trans. Image Process., 2003)

Signal recovery from random projections. - Emmanuel J. Candès; Justin K. Romberg (Computational Imaging, 2005)

Error Correction via Linear Programming. - Emmanuel J. Candès; Mark Rudelson; Terence Tao; Roman Vershynin (FOCS, 2005)

Decoding by linear programming. - Emmanuel J. Candès; Terence Tao (IEEE Trans. Inf. Theory, 2005)

Encoding the ell_p Ball from Limited Measurements. - Emmanuel J. Candès; Justin K. Romberg (DCC, 2006)

Robust Signal Recovery from Incomplete Observations. - Emmanuel J. Candès; Justin K. Romberg (ICIP, 2006)

Highly robust error correction by convex programming - Emmanuel J. Candès; Paige A. Randall (CoRR, 2006)

Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions. - Emmanuel J. Candès; Justin K. Romberg (Found. Comput. Math., 2006)

Fast geodesics computation with the phase flow method. - Lexing Ying; Emmanuel J. Candès (J. Comput. Phys., 2006)

The phase flow method. - Lexing Ying; Emmanuel J. Candès (J. Comput. Phys., 2006)

Fast Discrete Curvelet Transforms. - Emmanuel J. Candès; Laurent Demanet; David L. Donoho; Lexing Ying (Multiscale Model. Simul., 2006)

Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. - Emmanuel J. Candès; Justin K. Romberg; Terence Tao (IEEE Trans. Inf. Theory, 2006)

Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? - Emmanuel J. Candès; Terence Tao (IEEE Trans. Inf. Theory, 2006)

Sparse Signal and Image Recovery from Compressive Samples. - Emmanuel J. Candès; Nathaniel Braun; Michael B. Wakin (ISBI, 2007)

Errata for Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions. - Emmanuel J. Candès; Justin K. Romberg (Found. Comput. Math., 2007)

Fast Computation of Fourier Integral Operators. - Emmanuel J. Candès; Laurent Demanet; Lexing Ying (SIAM J. Sci. Comput., 2007)

Session TA1b: Compressive sensing. - Emmanuel J. Candès (ACSCC, 2008)

Compressed sensing and robust recovery of low rank matrices. - Maryam Fazel; Emmanuel J. Candès; Ben Recht; Pablo A. Parrilo (ACSCC, 2008)

Exact low-rank matrix completion via convex optimization. - Emmanuel J. Candès; Benjamin Recht (Allerton, 2008)

Compressive Sampling [From the Guest Editors]. - Richard G. Baraniuk; Emmanuel J. Candès; Robert D. Nowak; Martin Vetterli (IEEE Signal Process. Mag., 2008)

An Introduction To Compressive Sampling. - Emmanuel J. Candès; Michael B. Wakin (IEEE Signal Process. Mag., 2008)

Highly Robust Error Correction byConvex Programming. - Emmanuel J. Candès; Paige A. Randall (IEEE Trans. Inf. Theory, 2008)

Accurate low-rank matrix recovery from a small number of linear measurements. - Emmanuel J. Candès; Yaniv Plan (Allerton, 2009)

A fast and accurate first-order algorithm for compressed sensing. - Jérôme Bobin; Emmanuel J. Candès (ICIP, 2009)

A Fast Butterfly Algorithm for the Computation of Fourier Integral Operators. - Emmanuel J. Candès; Laurent Demanet; Lexing Ying (Multiscale Model. Simul., 2009)

Dense error correction for low-rank matrices via Principal Component Pursuit. - Arvind Ganesh; John Wright 001; Xiaodong Li 005; Emmanuel J. Candès; Yi Ma 001 (ISIT, 2010)

Stable Principal Component Pursuit. - Zihan Zhou 001; Xiaodong Li 005; John Wright 001; Emmanuel J. Candès; Yi Ma 001 (ISIT, 2010)

The Power of Convex Relaxation: The Surprising Stories of Matrix Completion and Compressed Sensing. - Emmanuel J. Candès (SODA, 2010)

Tight oracle bounds for low-rank matrix recovery from a minimal number of random measurements - Emmanuel J. Candès; Yaniv Plan (CoRR, 2010)

Compressed Sensing with Coherent and Redundant Dictionaries - Emmanuel J. Candès; Yonina C. Eldar; Deanna Needell (CoRR, 2010)

Applications of Sparse Representation and Compressive Sensing. - Richard G. Baraniuk; Emmanuel J. Candès; Michael Elad; Yi Ma 001 (Proc. IEEE, 2010)

Matrix Completion With Noise. - Emmanuel J. Candès; Yaniv Plan (Proc. IEEE, 2010)

A Singular Value Thresholding Algorithm for Matrix Completion. - Jian-Feng Cai 001; Emmanuel J. Candès; Zuowei Shen (SIAM J. Optim., 2010)

Compressed Sensing With Quantized Measurements. - Argyrios Zymnis; Stephen P. Boyd; Emmanuel J. Candès (IEEE Signal Process. Lett., 2010)

The power of convex relaxation: near-optimal matrix completion. - Emmanuel J. Candès; Terence Tao (IEEE Trans. Inf. Theory, 2010)

How well can we estimate a sparse vector? - Emmanuel J. Candès; Mark A. Davenport (CoRR, 2011)

Simple Bounds for Low-complexity Model Reconstruction - Emmanuel J. Candès; Benjamin Recht (CoRR, 2011)

PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming - Emmanuel J. Candès; Thomas Strohmer; Vladislav Voroninski (CoRR, 2011)

A Geometric Analysis of Subspace Clustering with Outliers - Mahdi Soltanolkotabi; Emmanuel J. Candès (CoRR, 2011)

Robust principal component analysis? - Emmanuel J. Candès; Xiaodong Li 005; Yi Ma 001; John Wright 001 (J. ACM, 2011)

Templates for convex cone problems with applications to sparse signal recovery. - Stephen Becker; Emmanuel J. Candès; Michael C. Grant (Math. Program. Comput., 2011)

NESTA: A Fast and Accurate First-Order Method for Sparse Recovery. - Stephen Becker; Jérôme Bobin; Emmanuel J. Candès (SIAM J. Imaging Sci., 2011)

Tight Oracle Inequalities for Low-Rank Matrix Recovery From a Minimal Number of Noisy Random Measurements. - Emmanuel J. Candès; Yaniv Plan (IEEE Trans. Inf. Theory, 2011)

A Probabilistic and RIPless Theory of Compressed Sensing. - Emmanuel J. Candès; Yaniv Plan (IEEE Trans. Inf. Theory, 2011)

Design and implementation of a fully integrated compressed-sensing signal acquisition system. - Juhwan Yoo; Stephen Becker; Manuel Monge; Matthew Loh; Emmanuel J. Candès; Azita Emami-Neyestanak (ICASSP, 2012)

Exact matrix completion via convex optimization. - Emmanuel J. Candès; Benjamin Recht (Commun. ACM, 2012)

Towards a Mathematical Theory of Super-Resolution - Emmanuel J. Candès; Carlos Fernandez-Granda (CoRR, 2012)

A single-photon sampling architecture for solid-state imaging - Ewout van den Berg; Emmanuel J. Candès; Garry Chinn; Craig S. Levin; Peter D. Olcott; Carlos A. Sing-Long (CoRR, 2012)

Super-Resolution from Noisy Data - Emmanuel J. Candès; Carlos Fernandez-Granda (CoRR, 2012)

Discussion: Latent variable graphical model selection via convex optimization - Emmanuel J. Candès; Mahdi Soltanolkotabi (CoRR, 2012)

A Nonuniform Sampler for Wideband Spectrally-Sparse Environments. - Michael B. Wakin; Stephen Becker; Eric B. Nakamura; Michael C. Grant; Emilio A. Sovero; Daniel Ching; Juhwan Yoo; Justin K. Romberg; Azita Emami-Neyestanak; Emmanuel J. Candès (IEEE J. Emerg. Sel. Topics Circuits Syst., 2012)

A Compressed Sensing Parameter Extraction Platform for Radar Pulse Signal Acquisition. - Juhwan Yoo; Christopher K. Turnes; Eric B. Nakamura; Chi K. Le; Stephen Becker; Emilio A. Sovero; Michael B. Wakin; Michael C. Grant; Justin K. Romberg; Azita Emami-Neyestanak; Emmanuel J. Candès (IEEE J. Emerg. Sel. Topics Circuits Syst., 2012)

Compressive sensing: Principles and hardware implementations. - Emmanuel J. Candès; Stephen Becker (ESSCIRC, 2013)

Super-resolution via Transform-Invariant Group-Sparse Regularization. - Carlos Fernandez-Granda; Emmanuel J. Candès (ICCV, 2013)

Phase Retrieval from masked Fourier transforms. - Emmanuel J. Candès; Xiaodong Li 005; Mahdi Soltanolkotabi (CoRR, 2013)

Hyperspectral fluorescence microscopy based on Compressive Sampling. - Makhlad Chahid; Jérôme Bobin; Hamed Shams Mousavi; Emmanuel J. Candès; Maxime Dahan; Vincent Studer (CoRR, 2013)

Robust Subspace Clustering - Mahdi Soltanolkotabi; Ehsan Elhamifar; Emmanuel J. Candès (CoRR, 2013)

Simple bounds for recovering low-complexity models. - Emmanuel J. Candès; Benjamin Recht (Math. Program., 2013)

On the Fundamental Limits of Adaptive Sensing. - Ery Arias-Castro; Emmanuel J. Candès; Mark A. Davenport (IEEE Trans. Inf. Theory, 2013)

Unbiased Risk Estimates for Singular Value Thresholding and Spectral Estimators. - Emmanuel J. Candès; Carlos A. Sing-Long; Joshua D. Trzasko (IEEE Trans. Signal Process., 2013)

Solving Quadratic Equations via PhaseLift When There Are About as Many Equations as Unknowns. - Emmanuel J. Candès; Xiaodong Li 005 (Found. Comput. Math., 2014)

Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems. - Yuxin Chen 002; Emmanuel J. Candès (NIPS, 2015)

Randomized Algorithms for Low-Rank Matrix Factorizations: Sharp Performance Bounds. - Rafi Witten; Emmanuel J. Candès (Algorithmica, 2015)

SLOPE is Adaptive to Unknown Sparsity and Asymptotically Minimax. - Emmanuel J. Candès; Weijie Su 001 (CoRR, 2015)

False Discoveries Occur Early on the Lasso Path. - Weijie Su 001; Malgorzata Bogdan; Emmanuel J. Candès (CoRR, 2015)

Adaptive Restart for Accelerated Gradient Schemes. - Brendan O'Donoghue; Emmanuel J. Candès (Found. Comput. Math., 2015)

Phase Retrieval via Matrix Completion. - Emmanuel J. Candès; Yonina C. Eldar; Thomas Strohmer; Vladislav Voroninski (SIAM Rev., 2015)

Phase Retrieval via Wirtinger Flow: Theory and Algorithms. - Emmanuel J. Candès; Xiaodong Li 005; Mahdi Soltanolkotabi (IEEE Trans. Inf. Theory, 2015)

The Projected Power Method: An Efficient Algorithm for Joint Alignment from Pairwise Differences. - Yuxin Chen 002; Emmanuel J. Candès (CoRR, 2016)

A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights. - Weijie Su 001; Stephen P. Boyd; Emmanuel J. Candès (J. Mach. Learn. Res., 2016)

Super-Resolution of Positive Sources: The Discrete Setup. - Veniamin I. Morgenshtern; Emmanuel J. Candès (SIAM J. Imaging Sci., 2016)

The Likelihood Ratio Test in High-Dimensional Logistic Regression Is Asymptotically a Rescaled Chi-Square. - Pragya Sur; Yuxin Chen 002; Emmanuel J. Candès (CoRR, 2017)

Conformalized Quantile Regression. - Yaniv Romano; Evan Patterson; Emmanuel J. Candès (NeurIPS, 2019)

Conformal Prediction Under Covariate Shift. - Ryan J. Tibshirani; Rina Foygel Barber; Emmanuel J. Candès; Aaditya Ramdas (NeurIPS, 2019)

Holographic Phase Retrieval and Optimal Reference Design. - David A. Barmherzig; Ju Sun; Emmanuel J. Candès; T. J. Lane; Po-Nan Li (CoRR, 2019)

Dual-Reference Design for Holographic Coherent Diffraction Imaging. - David A. Barmherzig; Ju Sun; Emmanuel J. Candès; T. J. Lane; Po-Nan Li (CoRR, 2019)

With Malice Towards None: Assessing Uncertainty via Equalized Coverage. - Yaniv Romano; Rina Foygel Barber; Chiara Sabatti; Emmanuel J. Candès (CoRR, 2019)

Achieving Equalized Odds by Resampling Sensitive Attributes. - Yaniv Romano; Stephen Bates; Emmanuel J. Candès (NeurIPS, 2020)

Classification with Valid and Adaptive Coverage. - Yaniv Romano; Matteo Sesia; Emmanuel J. Candès (NeurIPS, 2020)

Adaptive Conformal Inference Under Distribution Shift. - Isaac Gibbs; Emmanuel J. Candès (NeurIPS, 2021)

Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control. - Anastasios N. Angelopoulos; Stephen Bates; Emmanuel J. Candès; Michael I. Jordan; Lihua Lei (CoRR, 2021)

ReLU Neural Networks Learn the Simplest Models: Neural Isometry and Exact Recovery. - Yifei Wang 005; Yixuan Hua; Emmanuel J. Candès; Mert Pilanci (CoRR, 2022)

Interpretable Classification of Bacterial Raman Spectra With Knockoff Wavelets. - Charmaine Chia; Matteo Sesia; Chi-Sing Ho; Stefanie S. Jeffrey; Jennifer A. Dionne; Emmanuel J. Candès; Roger T. Howe (IEEE J. Biomed. Health Informatics, 2022)

Conformal PID Control for Time Series Prediction. - Anastasios Angelopoulos; Emmanuel J. Candès; Ryan J. Tibshirani (NeurIPS, 2023)

Uncertainty Quantification over Graph with Conformalized Graph Neural Networks. - Kexin Huang; Ying Jin; Emmanuel J. Candès; Jure Leskovec (NeurIPS, 2023)

Cross-Prediction-Powered Inference. - Tijana Zrnic; Emmanuel J. Candès (CoRR, 2023)

Selection by Prediction with Conformal p-values. - Ying Jin; Emmanuel J. Candès (J. Mach. Learn. Res., 2023)

Tractable Evaluation of Stein's Unbiased Risk Estimate With Convex Regularizers. - Parth Nobel; Emmanuel J. Candès; Stephen P. Boyd (IEEE Trans. Signal Process., 2023)

Active Statistical Inference. - Tijana Zrnic; Emmanuel J. Candès (ICML, 2024)

Large language model validity via enhanced conformal prediction methods. - John J. Cherian; Isaac Gibbs; Emmanuel J. Candès (NeurIPS, 2024)

Boosted Conformal Prediction Intervals. - Ran Xie; Rina Barber; Emmanuel J. Candès (NeurIPS, 2024)

Bellman Conformal Inference: Calibrating Prediction Intervals For Time Series. - Zitong Yang; Emmanuel J. Candès; Lihua Lei (CoRR, 2024)

A Library of Mirrors: Deep Neural Nets in Low Dimensions are Convex Lasso Models with Reflection Features. - Emi Zeger; Yifei Wang 005; Aaron Mishkin; Tolga Ergen; Emmanuel J. Candès; Mert Pilanci (CoRR, 2024)

RandALO: Out-of-sample risk estimation in no time flat. - Parth Nobel; Daniel LeJeune; Emmanuel J. Candès (CoRR, 2024)

Statistical Inference for Fairness Auditing. - John J. Cherian; Emmanuel J. Candès (J. Mach. Learn. Res., 2024)

Conformal Inference for Online Prediction with Arbitrary Distribution Shifts. - Isaac Gibbs; Emmanuel J. Candès (J. Mach. Learn. Res., 2024)

Synthetic continued pretraining. - Zitong Yang; Neil Band; Shuangping Li; Emmanuel J. Candès; Tatsunori Hashimoto (ICLR, 2025)

Can Unconfident LLM Annotations Be Used for Confident Conclusions? - Kristina Gligoric; Tijana Zrnic; Cinoo Lee; Emmanuel J. Candès; Dan Jurafsky (NAACL (Long Papers), 2025)

s1: Simple test-time scaling. - Niklas Muennighoff; Zitong Yang; Weijia Shi; Xiang Lisa Li; Li Fei-Fei 001; Hannaneh Hajishirzi; Luke Zettlemoyer; Percy Liang; Emmanuel J. Candès; Tatsunori Hashimoto (CoRR, 2025)

Automated Hypothesis Validation with Agentic Sequential Falsifications. - Kexin Huang; Ying Jin; Ryan Li; Michael Y. Li; Emmanuel J. Candès; Jure Leskovec (CoRR, 2025)

Overparameterized ReLU Neural Networks Learn the Simplest Model: Neural Isometry and Phase Transitions. - Yifei Wang 005; Yixuan Hua; Emmanuel J. Candès; Mert Pilanci (IEEE Trans. Inf. Theory, 2025)

Probably Approximately Correct Labels. - Emmanuel J. Candès; Andrew Ilyas; Tijana Zrnic (CoRR, 2025)