2026 Alyson K. Fletcher: Computer Science Researcher – H-Index, Publications & Awards

Overview

Alyson K. Fletcher is affiliated with the University of California, Los Angeles in the United States. Their research contributions span multiple areas within computer science and engineering, with a focus on both theoretical and applied topics.

The main fields of study associated with their work are:

Computer Science
Engineering

Their subfields of study include:

Artificial Intelligence
Biomedical Engineering
Statistical and Nonlinear Physics
Computational Mechanics
Human-Computer Interaction

The main research topics covered by Alyson K. Fletcher are diverse and reflect a strong emphasis on computational models and signal processing techniques. These topics are:

Stochastic Gradient Optimization Techniques
Neural Networks and Applications
Muscle activation and electromyography studies
Gaussian Processes and Bayesian Inference
Sparse and Compressive Sensing Techniques
Model Reduction and Neural Networks
Advanced Sensor and Energy Harvesting Materials

Frequently collaborating with other researchers, Alyson K. Fletcher works notably with:

Sundeep Rangan
Parthe Pandit
Mojtaba Sahraee-Ardakan
Golara Ahmadi Azar
Qin Hu

Their publication record spans multiple venues, with frequent contributions to:

arXiv (Cornell University)
IEEE Journal on Selected Areas in Information Theory
IEEE Journal of Selected Topics in Signal Processing
IEEE Sensors Journal
Journal of Statistical Mechanics Theory and Experiment

Some of their recent papers include:

"ViT-MDHGR: Cross-Day Reliability and Agility in Dynamic Hand Gesture Prediction via HD-sEMG Signal Decoding" (2024), published in IEEE Journal of Selected Topics in Signal Processing
"Inference With Deep Generative Priors in High Dimensions" (2020), published in IEEE Journal on Selected Areas in Information Theory
"Generalized Autoregressive Linear Models for Discrete High-Dimensional Data" (2020), published in IEEE Journal on Selected Areas in Information Theory
"Instability and Local Minima in GAN Training with Kernel Discriminators" (2022), published on arXiv (Cornell University)
"Inference in Multi-Layer Networks with Matrix-Valued Unknowns" (2020), published on arXiv (Cornell University)

Best Publications

Vector Approximate Message Passing

Sundeep Rangan;Philip Schniter;Alyson K. Fletcher

905
Citations
Compressive Sampling and Lossy Compression

V.K. Goyal;A.K. Fletcher;S. Rangan

331
Citations
Necessary and Sufficient Conditions for Sparsity Pattern Recovery

A.K. Fletcher;S. Rangan;V.K. Goyal

269
Citations
On the Convergence of Approximate Message Passing With Arbitrary Matrices

Sundeep Rangan;Philip Schniter;Alyson K. Fletcher;Subrata Sarkar

258
Citations
Asymptotic Analysis of MAP Estimation via the Replica Method and Applications to Compressed Sensing

S. Rangan;A. K. Fletcher;V. K. Goyal

231
Citations
Necessary and Sufficient Conditions on Sparsity Pattern Recovery

Alyson K. Fletcher;Sundeep Rangan;Vivek K. Goyal

229
Citations
Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing

Sundeep Rangan;Vivek Goyal;Alyson K Fletcher

197
Citations
Vector approximate message passing for the generalized linear model

Philip Schniter;Sundeep Rangan;Alyson K. Fletcher

137
Citations
Robust Predictive Quantization: Analysis and Design Via Convex Optimization

A.K. Fletcher;S. Rangan;V.K. Goyal;K. Ramchandran

128
Citations
On the convergence of approximate message passing with arbitrary matrices

Sundeep Rangan;Philip Schniter;Alyson K. Fletcher

120
Citations
On-off random access channels: A compressed sensing framework

Alyson K. Fletcher;Sundeep Rangan;Vivek K Goyal

109
Citations
Estimation from lossy sensor data: jump linear modeling and Kalman filtering

Alyson K. Fletcher;Sundeep Rangan;Vivek K. Goyal

106
Citations
Fixed Points of Generalized Approximate Message Passing With Arbitrary Matrices

Sundeep Rangan;Philip Schniter;Erwin Riegler;Alyson K. Fletcher

100
Citations
Approximate Message Passing With Consistent Parameter Estimation and Applications to Sparse Learning

Ulugbek S. Kamilov;Sundeep Rangan;Alyson K. Fletcher;Michael Unser

97
Citations
Iterative estimation of constrained rank-one matrices in noise

Sundeep Rangan;Alyson K. Fletcher

88
Citations
Denoising by sparse approximation: error bounds based on rate-distortion theory

Alyson K. Fletcher;Sundeep Rangan;Vivek K. Goyal;Kannan Ramchandran

80
Citations
Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization

Sundeep Rangan;Alyson K. Fletcher;Philip Schniter;Ulugbek S. Kamilov

76
Citations
Plug in estimation in high dimensional linear inverse problems a rigorous analysis

Alyson K Fletcher;Parthe Pandit;Sundeep Rangan;Subrata Sarkar

76
Citations
On the Rate-Distortion Performance of Compressed Sensing

A. K. Fletcher;S. Rangan;V. K. Goyal

73
Citations
Hybrid Approximate Message Passing

Sundeep Rangan;Alyson K. Fletcher;Vivek K. Goyal;Evan Byrne

67
Citations